system

Abstract

Provide a system. The method includes: a means for a user to input health-related questions on a user terminal; A means for transmitting question data from a user terminal to a server; A means for acquiring user information from a user database based on the user ID in the server; means for generating customized answers based on the question data and user information using an artificial intelligence model; means for transmitting the customized response to the user terminal; means for displaying the customized answer at the user terminal; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, there has been an increasing demand for online health information and health consultations. However, it is difficult to provide personalized answers based on each user's health condition and medical history. Furthermore, conventional systems can only provide standard answers and are unable to provide optimal advice for each user. Therefore, there is a need for a system that can provide customized health advice based on each user's health condition and lifestyle habits. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: A system including a means for a user to input a health-related question into a user terminal, a means for transmitting the question data from the user terminal to a server, a means for acquiring user information from a user database based on a user ID in the server, a means for generating a customized answer based on the question data and the user information using an artificial intelligence model, a means for transmitting the customized answer to the user terminal, and a means for displaying the customized answer on the user terminal can be provided, thereby making it possible to quickly provide specific and appropriate health advice tailored to the individual health condition and medical history of the user.

[0006] "User terminal" means a device used by a user that has the ability to input health-related questions, communicate with a server, and display customized answers.

[0007] "Question data" refers to the content of health-related questions entered by the user using the terminal.

[0008] The "server" is a system that receives question data sent from a user terminal, acquires user information, generates customized answers using an artificial intelligence model, and sends the answers to the user terminal.

[0009] "User ID" means an identifier used to uniquely identify a user.

[0010] A "user database" is a database that stores individual information about users (e.g., age, gender, medical history, etc.).

[0011] "User information" refers to information stored in the user database, such as the user's individual health condition and medical history.

[0012] An "artificial intelligence model" is an algorithm or system that uses technologies such as large-scale language models to generate customized answers based on question data and user information.

[0013] "Customized answers" are answers generated by an artificial intelligence model that are appropriate for a specific user based on the user's individual health status and medical history.

[0014] A "prompt" is an input sentence generated to input question data and user information into an artificial intelligence model. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health status and medical history. The system includes a user terminal, a server, and a back-end artificial intelligence model.

[0037] User Device

[0038] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0039] server

[0040] The server receives the question data sent from the user terminal. Once the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the subsequent artificial intelligence model.

[0041] Artificial Intelligence Model

[0042] The artificial intelligence model generates customized answers based on question data and user information using large-scale language models, etc. This model has an algorithm that generates the best answer for the input prompt. As a specific example, the AI ​​model may generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, sufficient sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0043] Sending answers to the user's device

[0044] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0045] Through the above process, the system of the present invention provides users with quick, accurate, and customized answers to their health-related questions, supporting their health management.

[0046] For example, if a user inputs the question, "Please tell me about the dietary precautions I should take as a diabetic," the system will provide optimal dietary advice taking into account the user's age, gender, medical history (diabetes), etc. For example, specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided.

[0047] In this way, the present invention can provide optimal health advice according to the health conditions and lifestyle habits that differ for each user.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The user types a health-related question into an input field displayed on the device's interface, for example, "How can I prevent catching a cold?"

[0051] Step 2:

[0052] The device receives the user's input and sends the question data to the server via a pre-configured API endpoint, along with the user ID.

[0053] Step 3:

[0054] The server receives a request from the user at the API endpoint and extracts the question data and user ID from the request body.

[0055] Step 4:

[0056] The server uses the user ID to retrieve relevant user information (e.g., age, gender, medical history, etc.) from a user database.

[0057] Step 5:

[0058] The server combines the acquired user information with the question data to generate a prompt to be passed to the artificial intelligence model.

[0059] Step 6:

[0060] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data and user information.

[0061] Step 7:

[0062] The server receives the customized answer from the artificial intelligence model and then generates a response to send back to the user device.

[0063] Step 8:

[0064] The device receives the response from the server and displays a customized answer to the user, such as, "If you are a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are especially important for preventing colds."

[0065] Through these steps, users can receive customized health advice.

[0066] Example 1

[0067] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0068] Conventional health advice systems do not fully consider the user's individual health condition or past medical history, and therefore can only provide general advice, which lacks specificity and effectiveness for users. In addition, inefficient data processing makes it difficult to provide users with appropriate answers quickly.

[0069] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0070] In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for generating customized answers based on question data and user information using a generative AI model, and means for transmitting the customized answers to a user terminal, thereby enabling the prompt provision of specific and effective health advice based on each user's individual health condition and medical history.

[0071] A "user terminal" is a device that allows a user to input a question, transmit the question to a server, and receive and display a response from the server.

[0072] The "server" is a computer system that receives question data sent from a user terminal, retrieves user information from a user database, inputs it into a generative AI model, generates customized answers, and sends them to the user terminal.

[0073] "User ID" is an identifier that uniquely identifies a user.

[0074] A "user database" is a database for storing information such as a user's age, gender, and medical history.

[0075] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate appropriate answers based on question data and user information.

[0076] "Question data" refers to data entered by a user in response to a health-related question.

[0077] A "customized answer" is a personalized answer generated by a generative AI model based on the user's individual information.

[0078] A "prompt" is input data for a generative AI model, and includes question data and user information.

[0079] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health condition and medical history. The system includes a user terminal, a server, and a generative AI model.

[0080] User Device

[0081] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0082] server

[0083] The server receives question data sent from the user terminal. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the generative AI model. Specifically, the question data and user information are integrated and provided to the generative AI model as a prompt sentence. An example of a prompt sentence is, "Please tell me how to prevent colds for a 30-year-old man with a history of asthma."

[0084] Generative AI Models

[0085] Generative AI models use large-scale language models and other tools to generate customized answers based on question data and user information. These models have algorithms that generate the best answer for the input prompt. For example, an AI model might generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0086] Sending answers to the user's device

[0087] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0088] Specific examples

[0089] For example, if a user inputs a question such as, "Please tell me what dietary advice I should take into account as a diabetic," the system will provide optimal dietary advice taking into account information such as the user's age, gender, and medical history (diabetes). Specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided. Another example of a prompt sentence to be input into the generative AI model is, "Please tell me what is an appropriate diet for a 50-year-old woman with diabetes."

[0090] In this way, the system of the present invention can provide optimal health advice tailored to each user's different health conditions and lifestyle habits, allowing users to receive prompt and accurate personalized health support.

[0091] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0092] Step 1: Enter a question on the user's device

[0093] A user inputs a question about their health through the interface of the user terminal. For example, they input a question such as "How can I prevent catching a cold?" into the text box. The input question data is generated.

[0094] Input: User's health question

[0095] Output: Question data (e.g., "How do I prevent catching a cold?")

[0096] Step 2: Send query data to the server

[0097] The user device sends the entered question data to the server. Specifically, this data is sent as an HTTP request to the server's API endpoint.

[0098] Input: Question data

[0099] Output: Request sent to server

[0100] Step 3: Retrieving User Information on the Server

[0101] The server analyzes the received question data and retrieves user information from the user database based on the user ID. This extracts information such as the user's age, gender, and medical history. For example, it retrieves information about a 30-year-old male who has a history of asthma.

[0102] Input: Question data, User ID

[0103] Output: User information (e.g., age, gender, medical history)

[0104] Step 4: Generate answers using a generative AI model

[0105] The server combines the question data and user information to create a prompt. For example, a prompt such as "Please tell me how to prevent colds for a 30-year-old male with a history of asthma." This prompt is input into a generative AI model. The generative AI model (e.g., GPT-4 (registered trademark)) generates a customized answer based on the input prompt.

[0106] Input: Question data, user information

[0107] Output: Generated answer (e.g., "To prevent colds, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowds.")

[0108] Step 5: Returning response data to the server

[0109] The server receives the response data generated by the generative AI model and formats it as needed. For example, it formats the response data in JSON format and saves it in the appropriate response format.

[0110] Input: Generated Answer

[0111] Output: Formatted response data

[0112] Step 6: Sending the response from the server to the user device

[0113] The server then sends the formatted response data to the user terminal. Specifically, the response data is sent as an HTTP response.

[0114] Input: Formatted response data

[0115] Output: Send the answer to the user's device

[0116] Step 7: Display the answer on the user's device

[0117] The user's device analyzes the received response data and displays it on the user interface. The user can then view specific and appropriate advice. For example, the user can see the following response on their device: "To prevent catching a cold, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowded places."

[0118] Input: Formatted response data

[0119] Output: Displayed answer

[0120] (Application example 1)

[0121] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] Conventional food delivery systems have the problem of making it difficult to choose the right meal because they do not offer personalized menu suggestions based on the user's health condition or dietary restrictions. Even systems that offer advice based on health information have the problem of not being able to follow up with specific food suggestions.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0124] In this invention, the server includes means for a user to input a health-related question at a user terminal, means for transmitting the question data from the user terminal to the server, means for retrieving user information from a user database based on a user ID at the server, means for generating a customized answer based on the question data and the user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for suggesting an appropriate menu based on the user information and the question data, and means for providing an interface for the user to order the suggested menu, thereby enabling appropriate menu selection based on the user's health condition and dietary restrictions and rapid ordering.

[0125] A "user terminal" is a device that allows a user to input health-related questions and display the answers.

[0126] "Question Data" refers to information about health-related questions entered by users.

[0127] A "server" is a device that has the function of receiving question data sent from a user and acquiring user information.

[0128] "User ID" is a unique identifier used to identify each user.

[0129] A "user database" is a database that holds information such as a user's age, gender, and medical history.

[0130] "User information" refers to detailed information about the user, such as their age, gender, and medical history.

[0131] An "artificial intelligence model" is an AI algorithm that generates customized answers based on question data and user information.

[0132] A "customized answer" is an answer generated based on the user's specific information (age, gender, medical history, etc.).

[0133] A "menu" is a selection of food or dishes suggested to a user.

[0134] An "interface" is the screen or operating means that a user uses to order the proposed menu.

[0135] The present invention is a system that allows users to input health-related questions and provides personalized health advice and appropriate meal menu suggestions based on the individual user's health condition and dietary restrictions. This system includes a user terminal, a server, and a back-end artificial intelligence model. The configuration and operation of the system are described in detail below.

[0136] User Device

[0137] The user terminal is a device such as a smartphone or tablet. The user can use the interface on this terminal to input health-related questions. For example, if the user inputs "What is the best diet to prevent colds?", the question is sent to the server. The terminal also has a function to display the answers and suggested menus sent from the server.

[0138] server

[0139] The server receives the question data sent from the user's device. Once the question data is received, the server retrieves user information (age, gender, medical history, etc.) from the user database based on the user ID. This user information and question data are then input into an artificial intelligence model to generate a customized answer.

[0140] Artificial Intelligence Model

[0141] The artificial intelligence model uses large-scale language models and other methods to generate customized answers based on question data and user information. This model has an algorithm that generates the best answer for the input prompt. An example of a generated answer is, "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds."

[0142] Sending answers to the user's device

[0143] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0144] Menu suggestions and interface

[0145] The system also includes a means to suggest appropriate meal options based on user information and question data. The suggested menu is displayed on the user's device, providing an interface for ordering directly. For example, specific meal options such as "chicken soup," "vegetable salad," and "steamed salmon and broccoli" are suggested.

[0146] Hardware and Software

[0147] The system uses the following hardware and software:

[0148] User devices: smartphones, tablets

[0149] Server: User information management and AI model execution

[0150] Software: Python, requests library, large-scale language models

[0151] Specific examples

[0152] For example, if a user types into the app, "What is the best diet to prevent colds?", the AI ​​model generates a customized answer: "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds." Suggested menu items such as "chicken soup" and "a salad with lots of vegetables" are then provided, which the user can order directly from their device.

[0153] (Example of a prompt to input to a generative AI model)

[0154] User ID: 12345

[0155] Q: What is the best diet to prevent colds?

[0156] User information: 30-year-old male with a history of asthma

[0157] The system allows users to easily obtain and order dietary advice and meal menus adapted to their individual health conditions.

[0158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0159] Step 1:

[0160] The user enters health-related questions into the device.

[0161] Input: A user asks a health-related question (e.g., "What is the best diet to prevent colds?")

[0162] Output: Input data displayed on the user's terminal

[0163] How it works: The user types a question through the interface of their smartphone or tablet, which the device then captures as data.

[0164] Step 2:

[0165] The user terminal sends the query data to the server.

[0166] Input: Question data entered by the user into the terminal

[0167] Output: The question data sent to the server

[0168] Specific operation: The terminal sends the question data entered by the user to the server as an HTTP request.

[0169] Step 3:

[0170] The server retrieves user information from the user database based on the user ID.

[0171] Input: User ID

[0172] Output: User information (age, gender, medical history, etc.)

[0173] Specific operation: The server executes a database query using the user ID in the request to obtain the corresponding user information.

[0174] Step 4:

[0175] The server combines the question data with user information and passes it to the artificial intelligence model.

[0176] Input: Question data, user information

[0177] Output: The prompt passed to the AI ​​model

[0178] Specific operation: The server combines the question data and user information into a single prompt sentence, and then inputs the prompt sentence into the artificial intelligence model.

[0179] Step 5:

[0180] An artificial intelligence model generates customized answers based on question data and user information.

[0181] Input: Prompt text (combined question data and user information)

[0182] Output: A customized answer (e.g., "A diet rich in vitamin C is particularly beneficial.")

[0183] What it does: The AI ​​model analyzes the prompt and runs an algorithm to generate the best answer.

[0184] Step 6:

[0185] The server sends the customized response to the user terminal.

[0186] Input: Customized Answer

[0187] Output: Customized answer data sent to the user's device

[0188] Specific operation: The server sends the generated answer to the user terminal as an HTTP response.

[0189] Step 7:

[0190] The user's device displays the customized answer.

[0191] Input: Customized answer data

[0192] Output: The answer that is displayed to the user.

[0193] Specific operation: The response data received by the device is displayed on the screen.

[0194] Step 8:

[0195] The server suggests an appropriate menu based on the user information and question data.

[0196] Input: User information, question data, generated answers

[0197] Output: Suggested menu items (e.g. "Chicken soup" or "Vegetable salad")

[0198] What it does: The server generates healthy menu options tailored to the user's information.

[0199] Step 9:

[0200] The user terminal displays the suggested menu and provides an interface for the user to place an order.

[0201] Input: Suggested menu

[0202] Output: The menu and ordering interface that is displayed on the user's screen.

[0203] Specific operation: Display the suggested menu and order button on the user's device, allowing the user to select a menu and place an order.

[0204] The above steps realize a system that allows users to receive customized advice in response to health-related questions and select and order a meal menu based on that advice.

[0205] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0206] The present invention provides a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end artificial intelligence model.

[0207] User Device

[0208] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0209] Emotion Engine

[0210] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input, tone of voice, facial expressions, etc. to generate emotional data for the user. For example, it can determine whether the user is feeling stressed or depressed.

[0211] server

[0212] The server receives question data and emotion data sent from the user device. Once the question data is received, the server retrieves user information from a user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[0213] Artificial Intelligence Model

[0214] The AI ​​model generates customized answers based on question data, user information, and sentiment data using large-scale language models. The model has algorithms that generate the best answer for the input prompt. For example, the AI ​​model generates customized answers such as:

[0215] If a user types, "How do I prevent catching a cold?" and the emotion engine recognizes that the user is feeling stressed, the AI ​​model will generate an answer with adjusted tone and content: "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0216] Sending answers to the user's device

[0217] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[0218] Through the above process, the system of the present invention takes into account the user's emotional state and provides quick, accurate, and customized answers to health-related questions, supporting the user's health management.

[0219] As a specific example, if a user inputs a question such as, "Please tell me what dietary precautions I should take as a diabetic," and the emotion engine recognizes that the user is worried, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[0220] In this way, the present invention can provide optimal health advice tailored to each user's health and emotional state.

[0221] The processing flow will be explained below.

[0222] Step 1:

[0223] The user types a health-related question into an input field displayed on the device's interface, for example, "How do I prevent catching a cold?"

[0224] Step 2:

[0225] The device receives the user's input and simultaneously uses an emotion engine to analyze the user's emotional state, which can be inferred from the input text data, voice tone, or facial expressions.

[0226] Step 3:

[0227] The device sends the question data and the user's emotion data to the server, including the user ID.

[0228] Step 4:

[0229] The server receives a request from a user at an API endpoint and extracts the question data, emotion data, and user ID from the request body.

[0230] Step 5:

[0231] The server uses the user ID to retrieve user information from a user database, including age, gender, medical history, etc.

[0232] Step 6:

[0233] The server combines the acquired user information, question data, and emotional data to generate prompts to pass to the AI ​​model, which include details about the user's health and emotional state.

[0234] Step 7:

[0235] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data, user information, and sentiment data.

[0236] Step 8:

[0237] The server receives customized answers from the artificial intelligence model, with content and tone tailored based on the user's emotional state.

[0238] Step 9:

[0239] The server generates a response to send the customized answer to the user terminal.

[0240] Step 10:

[0241] The device receives the response from the server and displays a customized answer to the user, such as, "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0242] Through these steps, users can receive customized health advice, which also takes into account the user's emotional state to provide better support.

[0243] Example 2

[0244] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0245] Today, there are many services that provide users with health information, but most only provide general information and few systems offer customized advice tailored to individual users' health and emotional states. Furthermore, while there is an increasing need for personalized advice that takes users' emotions into account, existing systems are limited in their ability to address this need. Therefore, there is a need for more accurate and personalized advice that takes into account the user's emotional state and individual health information.

[0246] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for integrating the acquired user information, question data, and emotion data to generate a prompt sentence to be input to the generative AI model, and means for generating a customized answer based on the question data, emotion data, and user information using the generative AI model. This makes it possible to quickly and accurately provide customized advice in response to a question entered by a user, taking into account the individual health condition and emotional state.

[0247] A "user terminal" is a device through which a user inputs health-related questions and communicates with the server.

[0248] "Question data" refers to data that indicates the content of health-related questions entered by the user.

[0249] "Emotional data" refers to data about a user's emotional state that is generated by analyzing the user's input, tone of voice, facial expressions, etc.

[0250] The "server" is a central processing unit for receiving question data and emotion data sent from a user terminal, generating prompt sentences based on the received data, and obtaining customized answers from the generative AI model.

[0251] "User ID" is an identifier that uniquely identifies a user.

[0252] A "user database" is a database that stores individual health information and medical history of users.

[0253] "User Information" refers to individual information necessary for providing health advice, such as the user's age, gender, and medical history.

[0254] A "prompt sentence" is a sentence format that integrates acquired user information, question data, and emotional data and is input into a generative AI model.

[0255] A "generative AI model" is an artificial intelligence model used to generate customized answers based on question data, emotion data, and user information.

[0256] "Customized answers" are personalized health advice generated using a generative AI model based on the user's individual information and emotional data.

[0257] The present invention is a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end generative AI model.

[0258] User Device

[0259] The user terminal is configured using a smartphone, computer, or similar device, and provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. It also has the function of receiving a customized answer from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?", the question is sent to the server.

[0260] Emotion Engine

[0261] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input content, voice tone, facial expressions, etc. to generate the user's emotion data. For example, it analyzes whether the user is feeling stressed when entering a question and generates this information as emotion data.

[0262] server

[0263] The server receives question data and emotion data sent from the user's device. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt sentence that is input into the generative AI model.

[0264] Specifically, the server generates a prompt like this:

[0265] If a user asks "How do I prevent catching a cold?" and the emotion engine detects "stress," provide a customized answer based on the user's information (age, gender, medical history).

[0266] Generative AI Models

[0267] A generative AI model uses a large-scale language model to generate customized answers based on question data, user information, and sentiment data. This model has an algorithm that generates the best answer for the input prompt. For example, the AI ​​model might generate a customized answer like this:

[0268] "Stress can increase your risk of catching a cold, so it's important to take time to relax, for example by doing deep breathing or yoga. It's also important to wash your hands properly and eat a balanced diet."

[0269] Sending answers to the user's device

[0270] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[0271] This system supports users in managing their health by allowing them to input health-related questions and providing quick and accurate customized answers that take into account their individual health and emotional state. For example, if a user inputs, "Please tell me about the diet I should be careful about as a diabetic," and the emotion engine recognizes the user's concerns, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[0272] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0273] Step 1:

[0274] User enters health questions

[0275] Input: User health question

[0276] Output: Question data

[0277] What happens: A user types a question into a smartphone or computer application: "How do I prevent catching a cold?"

[0278] Step 2:

[0279] The device sends the question data to the server.

[0280] Input: Question data, User ID

[0281] Output: Question data sent to the server

[0282] Specific operation: The user device sends the entered question to the server as an HTTP POST request. The sent data includes the question and the user ID.

[0283] Step 3:

[0284] The device generates emotion data using an emotion engine.

[0285] Input: User input, tone of voice, facial expressions, etc.

[0286] Output: Emotion data

[0287] How it works: The emotion engine analyzes the user's input, voice tone, and facial expressions to generate emotion data such as "stress" or "depression." The analysis results are sent to the server in JSON format.

[0288] Step 4:

[0289] The server receives the question data and emotion data.

[0290] Input: Question data, emotion data

[0291] Output: Question data and emotion data stored in a database on the server

[0292] Specific operation: The receiving API receives the data sent from the device and stores each piece of data in the database.

[0293] Step 5:

[0294] The server retrieves user information from the user database based on the user ID.

[0295] Input: User ID

[0296] Output: Obtained user information (age, gender, medical history, etc.)

[0297] Specific operation: Issues an SQL query to retrieve information such as the user's age, gender, and medical history from the database.

[0298] Step 6:

[0299] The server integrates question data, emotion data, and user information to generate prompt sentences to be input into the generative AI model.

[0300] Input: Question data, emotion data, user information

[0301] Output: prompt statement

[0302] Specific operation: The acquired data is integrated to generate a prompt sentence of the form, "If the user asks, 'How do I prevent a cold?' and the emotion engine recognizes the answer as 'stress,' provide a customized answer based on the user's information (age, gender, medical history)."

[0303] Step 7:

[0304] Server-generated prompts are fed into a generative AI model to obtain customized answers.

[0305] Input: prompt statement

[0306] Output: Customized answer

[0307] Specific operation: Sends a prompt to the API of the generated AI model via an HTTP POST request and receives the optimal answer from the AI ​​model.

[0308] Step 8:

[0309] The server generates the answer and sends it to the user's device.

[0310] Input: Customized Answer

[0311] Output: Answer sent to user terminal

[0312] Specific operation: A JSON containing the answer data is sent to the user's device as an HTTP response.

[0313] Step 9:

[0314] The user device displays a customized answer

[0315] Input: Customized Answer

[0316] Output: The answer shown to the user

[0317] Specific operation: The device displays the answer received from the server on the GUI, informing the user that "Stress can increase the risk of catching a cold, so it is important to take time to relax. For example, deep breathing or yoga are good ways to do this. It is also important to wash your hands properly and eat a balanced diet."

[0318] (Application example 2)

[0319] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0320] Conventional safety systems can only provide general advice, making it difficult to provide specific crime prevention advice tailored to the user's individual feelings and current situation. Therefore, it is necessary to improve the quality of information that helps users ensure their safety and provide more personalized crime prevention advice.

[0321] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0322] In this invention, the server includes means for a user to input a question at a user terminal, means for transmitting question data from the user terminal to the server, means for retrieving user information from an information database based on a user ID at the server, means for generating a customized answer based on the question data and user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for recognizing the user's emotions at the user terminal, means for retrieving the user's current location information, and means for generating a customized answer based on the question data, user information, emotions, and location information. This makes it possible to provide specific and appropriate crime prevention advice tailored to the user's current situation.

[0323] A "user terminal" is a device that provides an interface for a user to input questions or obtain emotion information.

[0324] "Question data" refers to data that indicates the content of a question entered by a user through a user terminal.

[0325] A "server" is a central computer system that processes query data, user information, emotion information, and location information.

[0326] "User information" refers to user attribute information obtained based on the user ID, including age, gender, medical history, etc.

[0327] "Emotional information" refers to data that indicates the user's emotional state, as analyzed from the user's input, tone of voice, facial expressions, etc.

[0328] "Location Information" is data that refers to a user's current geographic location.

[0329] An "artificial intelligence model" is a system with an algorithm that generates customized answers based on question data, user information, emotional information, and location information.

[0330] A "customized answer" is a specific answer to a user's question that is generated by taking into account user information, emotional information, and location information.

[0331] A "prompt" is a collection of data input to an artificial intelligence model, and refers to text that includes question data, user information, emotional information, and location information.

[0332] The present invention is a system that provides personalized crime prevention advice in response to a user's safety-related questions, taking into account the user's emotional information and location information. This system includes a "user terminal," an "emotion engine," a "server," and an "artificial intelligence model."

[0333] User Device

[0334] The user terminal takes the form of smart glasses. It provides an interface for users to input questions by voice and send the question data to the server. It also has the function of acquiring the user's emotional information and current location information. For example, if a user inputs a question such as "Is this area safe?", the voice data is collected.

[0335] Emotion Engine

[0336] The user device is equipped with an emotion engine that generates emotional information by analyzing the user's facial expressions and tone of voice, making it possible to understand the user's current emotional state, such as whether they are feeling anxious.

[0337] server

[0338] The server receives the question data, emotion information, and location information sent from the user terminal. The server then retrieves user information from the information database based on the user ID. The retrieved user information, emotion information, and location information are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[0339] Artificial Intelligence Model

[0340] The AI ​​model processes data using large-scale language models and other methods. The prompt includes question data, user information, emotional information, and location information. For example, if a user asks, "Is this area safe?" and the emotional engine recognizes that the user is feeling anxious, the AI ​​model will generate an answer with adjusted tone and content, such as, "The area around your current location is dangerous late at night. If you feel anxious, we recommend taking a taxi. The nearest taxi stand is ____."

[0341] Sending answers to the user's device

[0342] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate crime prevention advice based on their current situation and emotions.

[0343] Specific examples

[0344] Consider a case where a user is walking down a street at night and types the question "Is this area safe?" into their smart glasses. If the analysis indicates that the user is feeling uneasy, the server will use its AI model to generate a response such as "The area around your current location has a high crime rate. If you are uneasy, please use the nearest taxi stand (address: XXX)," and display this response on the smart glasses.

[0345] Prompt Sentence Examples

[0346] · Question: "Is this area safe?"

[0347] User information: age, gender, medical history, etc.

[0348] Emotional information: Anxiety

[0349] Location: Latitude 35.6895, Longitude 139.6917

[0350] By achieving the above, it becomes possible to provide specific and appropriate crime prevention advice that is tailored to the user's current situation.

[0351] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0352] Step 1:

[0353] The user types in a question.

[0354] Input: User voice question "Is this area safe?"

[0355] How it works: The user device converts speech into text data.

[0356] Output: Text data "Is this area safe?"

[0357] Step 2:

[0358] The user's device collects emotional information.

[0359] Input: User's voice tone and facial expressions

[0360] How it works: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state.

[0361] Output: Emotional information "anxiety"

[0362] Step 3:

[0363] The user device obtains the current location information.

[0364] Input: GPS sensor on the user device

[0365] How it works: The GPS sensor obtains the user's latitude and longitude.

[0366] Output: Location information "Latitude 35.6895, Longitude 139.6917"

[0367] Step 4:

[0368] The user terminal transmits question data, emotion information, and location information to the server.

[0369] Input: Question data, emotion information, location information

[0370] Operation: The user terminal sends these data to the server.

[0371] Output: Data package sent to the server

[0372] Step 5:

[0373] The server retrieves the user information.

[0374] Input: User ID

[0375] Operation: The server retrieves the corresponding user information from the information database.

[0376] Output: User information (e.g., age, gender, medical history, etc.)

[0377] Step 6:

[0378] The server consolidates the retrieved data and generates a prompt.

[0379] Input: Question data, user information, emotion information, location information

[0380] How it works: The server aggregates this data and creates prompts that are fed into an artificial intelligence model.

[0381] Output: Prompt "Is this area safe? User information: age, gender, current emotion (anxiety). Location information: latitude 35.6895, longitude 139.6917"

[0382] Step 7:

[0383] The server invokes the artificial intelligence model and provides the prompts.

[0384] Input: prompt

[0385] How it works: The server calls the artificial intelligence model and inputs a prompt.

[0386] Output: A customized answer from an artificial intelligence model

[0387] Step 8:

[0388] The server sends the customized response to the user terminal.

[0389] Input: Customized Answer

[0390] Operation: The server sends the generated answer to the user's device.

[0391] Output: The customized answer sent to the user's device

[0392] Step 9:

[0393] The user's device displays the customized answer.

[0394] Input: Customized Answer

[0395] Action: The user device displays the answer to the user visually or audibly.

[0396] Output: The user receives customized crime prevention advice.

[0397] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0398] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0399] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0400] [Second embodiment]

[0401] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0402] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0403] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0404] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0405] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0406] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0407] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0408] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0409] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0410] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0411] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0412] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0413] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health status and medical history. The system includes a user terminal, a server, and a back-end artificial intelligence model.

[0414] User Device

[0415] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0416] server

[0417] The server receives the question data sent from the user terminal. Once the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the subsequent artificial intelligence model.

[0418] Artificial Intelligence Model

[0419] The artificial intelligence model generates customized answers based on question data and user information using large-scale language models, etc. This model has an algorithm that generates the best answer for the input prompt. As a specific example, the AI ​​model may generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, sufficient sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0420] Sending answers to the user's device

[0421] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0422] Through the above process, the system of the present invention provides users with quick, accurate, and customized answers to their health-related questions, supporting their health management.

[0423] For example, if a user inputs the question, "Please tell me about the dietary precautions I should take as a diabetic," the system will provide optimal dietary advice taking into account the user's age, gender, medical history (diabetes), etc. For example, specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided.

[0424] In this way, the present invention can provide optimal health advice according to the health conditions and lifestyle habits that differ for each user.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] The user types a health-related question into an input field displayed on the device's interface, for example, "How can I prevent catching a cold?"

[0428] Step 2:

[0429] The device receives the user's input and sends the question data to the server via a pre-configured API endpoint, along with the user ID.

[0430] Step 3:

[0431] The server receives a request from the user at the API endpoint and extracts the question data and user ID from the request body.

[0432] Step 4:

[0433] The server uses the user ID to retrieve relevant user information (e.g., age, gender, medical history, etc.) from a user database.

[0434] Step 5:

[0435] The server combines the acquired user information with the question data to generate a prompt to be passed to the artificial intelligence model.

[0436] Step 6:

[0437] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data and user information.

[0438] Step 7:

[0439] The server receives the customized answer from the artificial intelligence model and then generates a response to send back to the user device.

[0440] Step 8:

[0441] The device receives the response from the server and displays a customized answer to the user, such as, "If you are a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are especially important for preventing colds."

[0442] Through these steps, users can receive customized health advice.

[0443] Example 1

[0444] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0445] Conventional health advice systems do not fully consider the user's individual health condition or past medical history, and therefore can only provide general advice, which lacks specificity and effectiveness for users. In addition, inefficient data processing makes it difficult to provide users with appropriate answers quickly.

[0446] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0447] In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for generating customized answers based on question data and user information using a generative AI model, and means for transmitting the customized answers to a user terminal, thereby enabling the prompt provision of specific and effective health advice based on each user's individual health condition and medical history.

[0448] A "user terminal" is a device that allows a user to input a question, transmit the question to a server, and receive and display a response from the server.

[0449] The "server" is a computer system that receives question data sent from a user terminal, retrieves user information from a user database, inputs it into a generative AI model, generates customized answers, and sends them to the user terminal.

[0450] "User ID" is an identifier that uniquely identifies a user.

[0451] A "user database" is a database for storing information such as a user's age, gender, and medical history.

[0452] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate appropriate answers based on question data and user information.

[0453] "Question data" refers to data entered by a user in response to a health-related question.

[0454] A "customized answer" is a personalized answer generated by a generative AI model based on the user's individual information.

[0455] A "prompt" is input data for a generative AI model, and includes question data and user information.

[0456] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health condition and medical history. The system includes a user terminal, a server, and a generative AI model.

[0457] User Device

[0458] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0459] server

[0460] The server receives question data sent from the user terminal. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the generative AI model. Specifically, the question data and user information are integrated and provided to the generative AI model as a prompt sentence. An example of a prompt sentence is, "Please tell me how to prevent colds for a 30-year-old man with a history of asthma."

[0461] Generative AI Models

[0462] Generative AI models use large-scale language models and other tools to generate customized answers based on question data and user information. These models have algorithms that generate the best answer for the input prompt. For example, an AI model might generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0463] Sending answers to the user's device

[0464] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0465] Specific examples

[0466] For example, if a user inputs a question such as, "Please tell me what dietary advice I should take into account as a diabetic," the system will provide optimal dietary advice taking into account information such as the user's age, gender, and medical history (diabetes). Specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided. Another example of a prompt sentence to be input into the generative AI model is, "Please tell me what is an appropriate diet for a 50-year-old woman with diabetes."

[0467] In this way, the system of the present invention can provide optimal health advice tailored to each user's different health conditions and lifestyle habits, allowing users to receive prompt and accurate personalized health support.

[0468] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0469] Step 1: Enter a question on the user's device

[0470] A user inputs a question about their health through the interface of the user terminal. For example, they input a question such as "How can I prevent catching a cold?" into the text box. The input question data is generated.

[0471] Input: User's health question

[0472] Output: Question data (e.g., "How do I prevent catching a cold?")

[0473] Step 2: Send query data to the server

[0474] The user device sends the entered question data to the server. Specifically, this data is sent as an HTTP request to the server's API endpoint.

[0475] Input: Question data

[0476] Output: Request sent to server

[0477] Step 3: Retrieving User Information on the Server

[0478] The server analyzes the received question data and retrieves user information from the user database based on the user ID. This extracts information such as the user's age, gender, and medical history. For example, it retrieves information about a 30-year-old male who has a history of asthma.

[0479] Input: Question data, User ID

[0480] Output: User information (e.g., age, gender, medical history)

[0481] Step 4: Generate answers using a generative AI model

[0482] The server combines the question data and user information to create a prompt. For example, a prompt such as "Please tell me how to prevent colds for a 30-year-old man with a history of asthma." This prompt is input into a generative AI model. The generative AI model (e.g., GPT-4) generates a customized answer based on the input prompt.

[0483] Input: Question data, user information

[0484] Output: Generated answer (e.g., "To prevent colds, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowds.")

[0485] Step 5: Returning response data to the server

[0486] The server receives the response data generated by the generative AI model and formats it as needed. For example, it formats the response data in JSON format and saves it in the appropriate response format.

[0487] Input: Generated Answer

[0488] Output: Formatted response data

[0489] Step 6: Sending the response from the server to the user device

[0490] The server then sends the formatted response data to the user terminal. Specifically, the response data is sent as an HTTP response.

[0491] Input: Formatted response data

[0492] Output: Send the answer to the user's device

[0493] Step 7: Display the answer on the user's device

[0494] The user's device analyzes the received response data and displays it on the user interface. The user can then view specific and appropriate advice. For example, the user can see the following response on their device: "To prevent catching a cold, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowded places."

[0495] Input: Formatted response data

[0496] Output: Displayed answer

[0497] (Application example 1)

[0498] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0499] Conventional food delivery systems have the problem of making it difficult to choose the right meal because they do not offer personalized menu suggestions based on the user's health condition or dietary restrictions. Even systems that offer advice based on health information have the problem of not being able to follow up with specific food suggestions.

[0500] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0501] In this invention, the server includes means for a user to input a health-related question at a user terminal, means for transmitting the question data from the user terminal to the server, means for retrieving user information from a user database based on a user ID at the server, means for generating a customized answer based on the question data and the user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for suggesting an appropriate menu based on the user information and the question data, and means for providing an interface for the user to order the suggested menu, thereby enabling appropriate menu selection based on the user's health condition and dietary restrictions and rapid ordering.

[0502] A "user terminal" is a device that allows a user to input health-related questions and display the answers.

[0503] "Question Data" refers to information about health-related questions entered by users.

[0504] A "server" is a device that has the function of receiving question data sent from a user and acquiring user information.

[0505] "User ID" is a unique identifier used to identify each user.

[0506] A "user database" is a database that holds information such as a user's age, gender, and medical history.

[0507] "User information" refers to detailed information about the user, such as their age, gender, and medical history.

[0508] An "artificial intelligence model" is an AI algorithm that generates customized answers based on question data and user information.

[0509] A "customized answer" is an answer generated based on the user's specific information (age, gender, medical history, etc.).

[0510] A "menu" is a selection of food or dishes suggested to a user.

[0511] An "interface" is the screen or operating means that a user uses to order the proposed menu.

[0512] The present invention is a system that allows users to input health-related questions and provides personalized health advice and appropriate meal menu suggestions based on the individual user's health condition and dietary restrictions. This system includes a user terminal, a server, and a back-end artificial intelligence model. The configuration and operation of the system are described in detail below.

[0513] User Device

[0514] The user terminal is a device such as a smartphone or tablet. The user can use the interface on this terminal to input health-related questions. For example, if the user inputs "What is the best diet to prevent colds?", the question is sent to the server. The terminal also has a function to display the answers and suggested menus sent from the server.

[0515] server

[0516] The server receives the question data sent from the user's device. Once the question data is received, the server retrieves user information (age, gender, medical history, etc.) from the user database based on the user ID. This user information and question data are then input into an artificial intelligence model to generate a customized answer.

[0517] Artificial Intelligence Model

[0518] The artificial intelligence model uses large-scale language models and other methods to generate customized answers based on question data and user information. This model has an algorithm that generates the best answer for the input prompt. An example of a generated answer is, "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds."

[0519] Sending answers to the user's device

[0520] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0521] Menu suggestions and interface

[0522] The system also includes a means to suggest appropriate meal options based on user information and question data. The suggested menu is displayed on the user's device, providing an interface for ordering directly. For example, specific meal options such as "chicken soup," "vegetable salad," and "steamed salmon and broccoli" are suggested.

[0523] Hardware and Software

[0524] The system uses the following hardware and software:

[0525] User devices: smartphones, tablets

[0526] Server: User information management and AI model execution

[0527] Software: Python, requests library, large-scale language models

[0528] Specific examples

[0529] For example, if a user types into the app, "What is the best diet to prevent colds?", the AI ​​model generates a customized answer: "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds." Suggested menu items such as "chicken soup" and "a salad with lots of vegetables" are then provided, which the user can order directly from their device.

[0530] (Example of a prompt to input to a generative AI model)

[0531] User ID: 12345

[0532] Q: What is the best diet to prevent colds?

[0533] User information: 30-year-old male with a history of asthma

[0534] The system allows users to easily obtain and order dietary advice and meal menus adapted to their individual health conditions.

[0535] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0536] Step 1:

[0537] The user enters health-related questions into the device.

[0538] Input: A user asks a health-related question (e.g., "What is the best diet to prevent colds?")

[0539] Output: Input data displayed on the user's terminal

[0540] How it works: The user types a question through the interface of their smartphone or tablet, which the device then captures as data.

[0541] Step 2:

[0542] The user terminal sends the query data to the server.

[0543] Input: Question data entered by the user into the terminal

[0544] Output: The question data sent to the server

[0545] Specific operation: The terminal sends the question data entered by the user to the server as an HTTP request.

[0546] Step 3:

[0547] The server retrieves user information from the user database based on the user ID.

[0548] Input: User ID

[0549] Output: User information (age, gender, medical history, etc.)

[0550] Specific operation: The server executes a database query using the user ID in the request to obtain the corresponding user information.

[0551] Step 4:

[0552] The server combines the question data with user information and passes it to the artificial intelligence model.

[0553] Input: Question data, user information

[0554] Output: The prompt passed to the AI ​​model

[0555] Specific operation: The server combines the question data and user information into a single prompt sentence, and then inputs the prompt sentence into the artificial intelligence model.

[0556] Step 5:

[0557] An artificial intelligence model generates customized answers based on question data and user information.

[0558] Input: Prompt text (combined question data and user information)

[0559] Output: A customized answer (e.g., "A diet rich in vitamin C is particularly beneficial.")

[0560] What it does: The AI ​​model analyzes the prompt and runs an algorithm to generate the best answer.

[0561] Step 6:

[0562] The server sends the customized response to the user terminal.

[0563] Input: Customized Answer

[0564] Output: Customized answer data sent to the user's device

[0565] Specific operation: The server sends the generated answer to the user terminal as an HTTP response.

[0566] Step 7:

[0567] The user's device displays the customized answer.

[0568] Input: Customized answer data

[0569] Output: The answer that is displayed to the user.

[0570] Specific operation: The response data received by the device is displayed on the screen.

[0571] Step 8:

[0572] The server suggests an appropriate menu based on the user information and question data.

[0573] Input: User information, question data, generated answers

[0574] Output: Suggested menu items (e.g. "Chicken soup" or "Vegetable salad")

[0575] What it does: The server generates healthy menu options tailored to the user's information.

[0576] Step 9:

[0577] The user terminal displays the suggested menu and provides an interface for the user to place an order.

[0578] Input: Suggested menu

[0579] Output: The menu and ordering interface that is displayed on the user's screen.

[0580] Specific operation: Display the suggested menu and order button on the user's device, allowing the user to select a menu and place an order.

[0581] The above steps realize a system that allows users to receive customized advice in response to health-related questions and select and order a meal menu based on that advice.

[0582] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0583] The present invention provides a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end artificial intelligence model.

[0584] User Device

[0585] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0586] Emotion Engine

[0587] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input, tone of voice, facial expressions, etc. to generate emotional data for the user. For example, it can determine whether the user is feeling stressed or depressed.

[0588] server

[0589] The server receives question data and emotion data sent from the user device. Once the question data is received, the server retrieves user information from a user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[0590] Artificial Intelligence Model

[0591] The AI ​​model generates customized answers based on question data, user information, and sentiment data using large-scale language models. The model has algorithms that generate the best answer for the input prompt. For example, the AI ​​model generates customized answers such as:

[0592] If a user types, "How do I prevent catching a cold?" and the emotion engine recognizes that the user is feeling stressed, the AI ​​model will generate an answer with adjusted tone and content: "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0593] Sending answers to the user's device

[0594] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[0595] Through the above process, the system of the present invention takes into account the user's emotional state and provides quick, accurate, and customized answers to health-related questions, supporting the user's health management.

[0596] As a specific example, if a user inputs a question such as, "Please tell me what dietary precautions I should take as a diabetic," and the emotion engine recognizes that the user is worried, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[0597] In this way, the present invention can provide optimal health advice tailored to each user's health and emotional state.

[0598] The processing flow will be explained below.

[0599] Step 1:

[0600] The user types a health-related question into an input field displayed on the device's interface, for example, "How do I prevent catching a cold?"

[0601] Step 2:

[0602] The device receives the user's input and simultaneously uses an emotion engine to analyze the user's emotional state, which can be inferred from the input text data, voice tone, or facial expressions.

[0603] Step 3:

[0604] The device sends the question data and the user's emotion data to the server, including the user ID.

[0605] Step 4:

[0606] The server receives a request from a user at an API endpoint and extracts the question data, emotion data, and user ID from the request body.

[0607] Step 5:

[0608] The server uses the user ID to retrieve user information from a user database, including age, gender, medical history, etc.

[0609] Step 6:

[0610] The server combines the acquired user information, question data, and emotional data to generate prompts to pass to the AI ​​model, which include details about the user's health and emotional state.

[0611] Step 7:

[0612] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data, user information, and sentiment data.

[0613] Step 8:

[0614] The server receives customized answers from the artificial intelligence model, with content and tone tailored based on the user's emotional state.

[0615] Step 9:

[0616] The server generates a response to send the customized answer to the user terminal.

[0617] Step 10:

[0618] The device receives the response from the server and displays a customized answer to the user, such as, "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0619] Through these steps, users can receive customized health advice, which also takes into account the user's emotional state to provide better support.

[0620] Example 2

[0621] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0622] Today, there are many services that provide users with health information, but most only provide general information and few systems offer customized advice tailored to individual users' health and emotional states. Furthermore, while there is an increasing need for personalized advice that takes users' emotions into account, existing systems are limited in their ability to address this need. Therefore, there is a need for more accurate and personalized advice that takes into account the user's emotional state and individual health information.

[0623] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for integrating the acquired user information, question data, and emotion data to generate a prompt sentence to be input to the generative AI model, and means for generating a customized answer based on the question data, emotion data, and user information using the generative AI model. This makes it possible to quickly and accurately provide customized advice in response to a question entered by a user, taking into account the individual health condition and emotional state.

[0624] A "user terminal" is a device through which a user inputs health-related questions and communicates with the server.

[0625] "Question data" refers to data that indicates the content of health-related questions entered by the user.

[0626] "Emotional data" refers to data about a user's emotional state that is generated by analyzing the user's input, tone of voice, facial expressions, etc.

[0627] The "server" is a central processing unit for receiving question data and emotion data sent from a user terminal, generating prompt sentences based on the received data, and obtaining customized answers from the generative AI model.

[0628] "User ID" is an identifier that uniquely identifies a user.

[0629] A "user database" is a database that stores individual health information and medical history of users.

[0630] "User Information" refers to individual information necessary for providing health advice, such as the user's age, gender, and medical history.

[0631] A "prompt sentence" is a sentence format that integrates acquired user information, question data, and emotional data and is input into a generative AI model.

[0632] A "generative AI model" is an artificial intelligence model used to generate customized answers based on question data, emotion data, and user information.

[0633] "Customized answers" are personalized health advice generated using a generative AI model based on the user's individual information and emotional data.

[0634] The present invention is a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end generative AI model.

[0635] User Device

[0636] The user terminal is configured using a smartphone, computer, or similar device, and provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. It also has the function of receiving a customized answer from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?", the question is sent to the server.

[0637] Emotion Engine

[0638] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input content, voice tone, facial expressions, etc. to generate the user's emotion data. For example, it analyzes whether the user is feeling stressed when entering a question and generates this information as emotion data.

[0639] server

[0640] The server receives question data and emotion data sent from the user's device. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt sentence that is input into the generative AI model.

[0641] Specifically, the server generates a prompt like this:

[0642] If a user asks "How do I prevent catching a cold?" and the emotion engine detects "stress," provide a customized answer based on the user's information (age, gender, medical history).

[0643] Generative AI Models

[0644] A generative AI model uses a large-scale language model to generate customized answers based on question data, user information, and sentiment data. This model has an algorithm that generates the best answer for the input prompt. For example, the AI ​​model might generate a customized answer like this:

[0645] "Stress can increase your risk of catching a cold, so it's important to take time to relax, for example by doing deep breathing or yoga. It's also important to wash your hands properly and eat a balanced diet."

[0646] Sending answers to the user's device

[0647] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[0648] This system supports users in managing their health by allowing them to input health-related questions and providing quick and accurate customized answers that take into account their individual health and emotional state. For example, if a user inputs, "Please tell me about the diet I should be careful about as a diabetic," and the emotion engine recognizes the user's concerns, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[0649] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0650] Step 1:

[0651] User enters health questions

[0652] Input: User health question

[0653] Output: Question data

[0654] What happens: A user types a question into a smartphone or computer application: "How do I prevent catching a cold?"

[0655] Step 2:

[0656] The device sends the question data to the server.

[0657] Input: Question data, User ID

[0658] Output: Question data sent to the server

[0659] Specific operation: The user device sends the entered question to the server as an HTTP POST request. The sent data includes the question and the user ID.

[0660] Step 3:

[0661] The device generates emotion data using an emotion engine.

[0662] Input: User input, tone of voice, facial expressions, etc.

[0663] Output: Emotion data

[0664] How it works: The emotion engine analyzes the user's input, voice tone, and facial expressions to generate emotion data such as "stress" or "depression." The analysis results are sent to the server in JSON format.

[0665] Step 4:

[0666] The server receives the question data and emotion data.

[0667] Input: Question data, emotion data

[0668] Output: Question data and emotion data stored in a database on the server

[0669] Specific operation: The receiving API receives the data sent from the device and stores each piece of data in the database.

[0670] Step 5:

[0671] The server retrieves user information from the user database based on the user ID.

[0672] Input: User ID

[0673] Output: Obtained user information (age, gender, medical history, etc.)

[0674] Specific operation: Issues an SQL query to retrieve information such as the user's age, gender, and medical history from the database.

[0675] Step 6:

[0676] The server integrates question data, emotion data, and user information to generate prompt sentences to be input into the generative AI model.

[0677] Input: Question data, emotion data, user information

[0678] Output: prompt statement

[0679] Specific operation: The acquired data is integrated to generate a prompt sentence of the form, "If the user asks, 'How do I prevent a cold?' and the emotion engine recognizes the answer as 'stress,' provide a customized answer based on the user's information (age, gender, medical history)."

[0680] Step 7:

[0681] Server-generated prompts are fed into a generative AI model to obtain customized answers.

[0682] Input: prompt statement

[0683] Output: Customized answer

[0684] Specific operation: Sends a prompt to the API of the generated AI model via an HTTP POST request and receives the optimal answer from the AI ​​model.

[0685] Step 8:

[0686] The server generates the answer and sends it to the user's device.

[0687] Input: Customized Answer

[0688] Output: Answer sent to user terminal

[0689] Specific operation: A JSON containing the answer data is sent to the user's device as an HTTP response.

[0690] Step 9:

[0691] The user device displays a customized answer

[0692] Input: Customized Answer

[0693] Output: The answer shown to the user

[0694] Specific operation: The device displays the answer received from the server on the GUI, informing the user that "Stress can increase the risk of catching a cold, so it is important to take time to relax. For example, deep breathing or yoga are good ways to do this. It is also important to wash your hands properly and eat a balanced diet."

[0695] (Application example 2)

[0696] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0697] Conventional safety systems can only provide general advice, making it difficult to provide specific crime prevention advice tailored to the user's individual feelings and current situation. Therefore, it is necessary to improve the quality of information that helps users ensure their safety and provide more personalized crime prevention advice.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0699] In this invention, the server includes means for a user to input a question at a user terminal, means for transmitting question data from the user terminal to the server, means for retrieving user information from an information database based on a user ID at the server, means for generating a customized answer based on the question data and user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for recognizing the user's emotions at the user terminal, means for retrieving the user's current location information, and means for generating a customized answer based on the question data, user information, emotions, and location information. This makes it possible to provide specific and appropriate crime prevention advice tailored to the user's current situation.

[0700] A "user terminal" is a device that provides an interface for a user to input questions or obtain emotion information.

[0701] "Question data" refers to data that indicates the content of a question entered by a user through a user terminal.

[0702] A "server" is a central computer system that processes query data, user information, emotion information, and location information.

[0703] "User information" refers to user attribute information obtained based on the user ID, including age, gender, medical history, etc.

[0704] "Emotional information" refers to data that indicates the user's emotional state, as analyzed from the user's input, tone of voice, facial expressions, etc.

[0705] "Location Information" is data that refers to a user's current geographic location.

[0706] An "artificial intelligence model" is a system with an algorithm that generates customized answers based on question data, user information, emotional information, and location information.

[0707] A "customized answer" is a specific answer to a user's question that is generated by taking into account user information, emotional information, and location information.

[0708] A "prompt" is a collection of data input to an artificial intelligence model, and refers to text that includes question data, user information, emotional information, and location information.

[0709] The present invention is a system that provides personalized crime prevention advice in response to a user's safety-related questions, taking into account the user's emotional information and location information. This system includes a "user terminal," an "emotion engine," a "server," and an "artificial intelligence model."

[0710] User Device

[0711] The user terminal takes the form of smart glasses. It provides an interface for users to input questions by voice and send the question data to the server. It also has the function of acquiring the user's emotional information and current location information. For example, if a user inputs a question such as "Is this area safe?", the voice data is collected.

[0712] Emotion Engine

[0713] The user device is equipped with an emotion engine that generates emotional information by analyzing the user's facial expressions and tone of voice, making it possible to understand the user's current emotional state, such as whether they are feeling anxious.

[0714] server

[0715] The server receives the question data, emotion information, and location information sent from the user terminal. The server then retrieves user information from the information database based on the user ID. The retrieved user information, emotion information, and location information are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[0716] Artificial Intelligence Model

[0717] The AI ​​model processes data using large-scale language models and other methods. The prompt includes question data, user information, emotional information, and location information. For example, if a user asks, "Is this area safe?" and the emotional engine recognizes that the user is feeling anxious, the AI ​​model will generate an answer with adjusted tone and content, such as, "The area around your current location is dangerous late at night. If you feel anxious, we recommend taking a taxi. The nearest taxi stand is ____."

[0718] Sending answers to the user's device

[0719] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate crime prevention advice based on their current situation and emotions.

[0720] Specific examples

[0721] Consider a case where a user is walking down a street at night and types the question "Is this area safe?" into their smart glasses. If the analysis indicates that the user is feeling uneasy, the server will use its AI model to generate a response such as "The area around your current location has a high crime rate. If you are uneasy, please use the nearest taxi stand (address: XXX)," and display this response on the smart glasses.

[0722] Prompt Sentence Examples

[0723] · Question: "Is this area safe?"

[0724] User information: age, gender, medical history, etc.

[0725] Emotional information: Anxiety

[0726] Location: Latitude 35.6895, Longitude 139.6917

[0727] By achieving the above, it becomes possible to provide specific and appropriate crime prevention advice that is tailored to the user's current situation.

[0728] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0729] Step 1:

[0730] The user types in a question.

[0731] Input: User voice question "Is this area safe?"

[0732] How it works: The user device converts speech into text data.

[0733] Output: Text data "Is this area safe?"

[0734] Step 2:

[0735] The user's device collects emotional information.

[0736] Input: User's voice tone and facial expressions

[0737] How it works: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state.

[0738] Output: Emotional information "anxiety"

[0739] Step 3:

[0740] The user device obtains the current location information.

[0741] Input: GPS sensor on the user device

[0742] How it works: The GPS sensor obtains the user's latitude and longitude.

[0743] Output: Location information "Latitude 35.6895, Longitude 139.6917"

[0744] Step 4:

[0745] The user terminal transmits question data, emotion information, and location information to the server.

[0746] Input: Question data, emotion information, location information

[0747] Operation: The user terminal sends these data to the server.

[0748] Output: Data package sent to the server

[0749] Step 5:

[0750] The server retrieves the user information.

[0751] Input: User ID

[0752] Operation: The server retrieves the corresponding user information from the information database.

[0753] Output: User information (e.g., age, gender, medical history, etc.)

[0754] Step 6:

[0755] The server consolidates the retrieved data and generates a prompt.

[0756] Input: Question data, user information, emotion information, location information

[0757] How it works: The server aggregates this data and creates prompts that are fed into an artificial intelligence model.

[0758] Output: Prompt "Is this area safe? User information: age, gender, current emotion (anxiety). Location information: latitude 35.6895, longitude 139.6917"

[0759] Step 7:

[0760] The server invokes the artificial intelligence model and provides the prompts.

[0761] Input: prompt

[0762] How it works: The server calls the artificial intelligence model and inputs a prompt.

[0763] Output: A customized answer from an artificial intelligence model

[0764] Step 8:

[0765] The server sends the customized response to the user terminal.

[0766] Input: Customized Answer

[0767] Operation: The server sends the generated answer to the user's device.

[0768] Output: The customized answer sent to the user's device

[0769] Step 9:

[0770] The user's device displays the customized answer.

[0771] Input: Customized Answer

[0772] Action: The user device displays the answer to the user visually or audibly.

[0773] Output: The user receives customized crime prevention advice.

[0774] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0775] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0776] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0777] [Third embodiment]

[0778] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0779] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0780] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0781] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0782] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0783] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0784] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0785] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0786] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0787] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0788] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0789] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0790] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health status and medical history. The system includes a user terminal, a server, and a back-end artificial intelligence model.

[0791] User Device

[0792] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0793] server

[0794] The server receives the question data sent from the user terminal. Once the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the subsequent artificial intelligence model.

[0795] Artificial Intelligence Model

[0796] The artificial intelligence model generates customized answers based on question data and user information using large-scale language models, etc. This model has an algorithm that generates the best answer for the input prompt. As a specific example, the AI ​​model may generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, sufficient sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0797] Sending answers to the user's device

[0798] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0799] Through the above process, the system of the present invention provides users with quick, accurate, and customized answers to their health-related questions, supporting their health management.

[0800] For example, if a user inputs the question, "Please tell me about the dietary precautions I should take as a diabetic," the system will provide optimal dietary advice taking into account the user's age, gender, medical history (diabetes), etc. For example, specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided.

[0801] In this way, the present invention can provide optimal health advice according to the health conditions and lifestyle habits that differ for each user.

[0802] The processing flow will be explained below.

[0803] Step 1:

[0804] The user types a health-related question into an input field displayed on the device's interface, for example, "How can I prevent catching a cold?"

[0805] Step 2:

[0806] The device receives the user's input and sends the question data to the server via a pre-configured API endpoint, along with the user ID.

[0807] Step 3:

[0808] The server receives a request from the user at the API endpoint and extracts the question data and user ID from the request body.

[0809] Step 4:

[0810] The server uses the user ID to retrieve relevant user information (e.g., age, gender, medical history, etc.) from a user database.

[0811] Step 5:

[0812] The server combines the acquired user information with the question data to generate a prompt to be passed to the artificial intelligence model.

[0813] Step 6:

[0814] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data and user information.

[0815] Step 7:

[0816] The server receives the customized answer from the artificial intelligence model and then generates a response to send back to the user device.

[0817] Step 8:

[0818] The device receives the response from the server and displays a customized answer to the user, such as, "If you are a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are especially important for preventing colds."

[0819] Through these steps, users can receive customized health advice.

[0820] Example 1

[0821] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0822] Conventional health advice systems do not fully consider the user's individual health condition or past medical history, and therefore can only provide general advice, which lacks specificity and effectiveness for users. In addition, inefficient data processing makes it difficult to provide users with appropriate answers quickly.

[0823] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0824] In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for generating customized answers based on question data and user information using a generative AI model, and means for transmitting the customized answers to a user terminal, thereby enabling the prompt provision of specific and effective health advice based on each user's individual health condition and medical history.

[0825] A "user terminal" is a device that allows a user to input a question, transmit the question to a server, and receive and display a response from the server.

[0826] The "server" is a computer system that receives question data sent from a user terminal, retrieves user information from a user database, inputs it into a generative AI model, generates customized answers, and sends them to the user terminal.

[0827] "User ID" is an identifier that uniquely identifies a user.

[0828] A "user database" is a database for storing information such as a user's age, gender, and medical history.

[0829] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate appropriate answers based on question data and user information.

[0830] "Question data" refers to data entered by a user in response to a health-related question.

[0831] A "customized answer" is a personalized answer generated by a generative AI model based on the user's individual information.

[0832] A "prompt" is input data for a generative AI model, and includes question data and user information.

[0833] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health condition and medical history. The system includes a user terminal, a server, and a generative AI model.

[0834] User Device

[0835] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0836] server

[0837] The server receives question data sent from the user terminal. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the generative AI model. Specifically, the question data and user information are integrated and provided to the generative AI model as a prompt sentence. An example of a prompt sentence is, "Please tell me how to prevent colds for a 30-year-old man with a history of asthma."

[0838] Generative AI Models

[0839] Generative AI models use large-scale language models and other tools to generate customized answers based on question data and user information. These models have algorithms that generate the best answer for the input prompt. For example, an AI model might generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[0840] Sending answers to the user's device

[0841] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0842] Specific examples

[0843] For example, if a user inputs a question such as, "Please tell me what dietary advice I should take into account as a diabetic," the system will provide optimal dietary advice taking into account information such as the user's age, gender, and medical history (diabetes). Specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided. Another example of a prompt sentence to be input into the generative AI model is, "Please tell me what is an appropriate diet for a 50-year-old woman with diabetes."

[0844] In this way, the system of the present invention can provide optimal health advice tailored to each user's different health conditions and lifestyle habits, allowing users to receive prompt and accurate personalized health support.

[0845] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0846] Step 1: Enter a question on the user's device

[0847] A user inputs a question about their health through the interface of the user terminal. For example, they input a question such as "How can I prevent catching a cold?" into the text box. The input question data is generated.

[0848] Input: User's health question

[0849] Output: Question data (e.g., "How do I prevent catching a cold?")

[0850] Step 2: Send query data to the server

[0851] The user device sends the entered question data to the server. Specifically, this data is sent as an HTTP request to the server's API endpoint.

[0852] Input: Question data

[0853] Output: Request sent to server

[0854] Step 3: Retrieving User Information on the Server

[0855] The server analyzes the received question data and retrieves user information from the user database based on the user ID. This extracts information such as the user's age, gender, and medical history. For example, it retrieves information about a 30-year-old male who has a history of asthma.

[0856] Input: Question data, User ID

[0857] Output: User information (e.g., age, gender, medical history)

[0858] Step 4: Generate answers using a generative AI model

[0859] The server combines the question data and user information to create a prompt. For example, a prompt such as "Please tell me how to prevent colds for a 30-year-old man with a history of asthma." This prompt is input into a generative AI model. The generative AI model (e.g., GPT-4) generates a customized answer based on the input prompt.

[0860] Input: Question data, user information

[0861] Output: Generated answer (e.g., "To prevent colds, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowds.")

[0862] Step 5: Returning response data to the server

[0863] The server receives the response data generated by the generative AI model and formats it as needed. For example, it formats the response data in JSON format and saves it in the appropriate response format.

[0864] Input: Generated Answer

[0865] Output: Formatted response data

[0866] Step 6: Sending the response from the server to the user device

[0867] The server then sends the formatted response data to the user terminal. Specifically, the response data is sent as an HTTP response.

[0868] Input: Formatted response data

[0869] Output: Send the answer to the user's device

[0870] Step 7: Display the answer on the user's device

[0871] The user's device analyzes the received response data and displays it on the user interface. The user can then view specific and appropriate advice. For example, the user can see the following response on their device: "To prevent catching a cold, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowded places."

[0872] Input: Formatted response data

[0873] Output: Displayed answer

[0874] (Application example 1)

[0875] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0876] Conventional food delivery systems have the problem of making it difficult to choose the right meal because they do not offer personalized menu suggestions based on the user's health condition or dietary restrictions. Even systems that offer advice based on health information have the problem of not being able to follow up with specific food suggestions.

[0877] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0878] In this invention, the server includes means for a user to input a health-related question at a user terminal, means for transmitting the question data from the user terminal to the server, means for retrieving user information from a user database based on a user ID at the server, means for generating a customized answer based on the question data and the user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for suggesting an appropriate menu based on the user information and the question data, and means for providing an interface for the user to order the suggested menu, thereby enabling appropriate menu selection based on the user's health condition and dietary restrictions and rapid ordering.

[0879] A "user terminal" is a device that allows a user to input health-related questions and display the answers.

[0880] "Question Data" refers to information about health-related questions entered by users.

[0881] A "server" is a device that has the function of receiving question data sent from a user and acquiring user information.

[0882] "User ID" is a unique identifier used to identify each user.

[0883] A "user database" is a database that holds information such as a user's age, gender, and medical history.

[0884] "User information" refers to detailed information about the user, such as their age, gender, and medical history.

[0885] An "artificial intelligence model" is an AI algorithm that generates customized answers based on question data and user information.

[0886] A "customized answer" is an answer generated based on the user's specific information (age, gender, medical history, etc.).

[0887] A "menu" is a selection of food or dishes suggested to a user.

[0888] An "interface" is the screen or operating means that a user uses to order the proposed menu.

[0889] The present invention is a system that allows users to input health-related questions and provides personalized health advice and appropriate meal menu suggestions based on the individual user's health condition and dietary restrictions. This system includes a user terminal, a server, and a back-end artificial intelligence model. The configuration and operation of the system are described in detail below.

[0890] User Device

[0891] The user terminal is a device such as a smartphone or tablet. The user can use the interface on this terminal to input health-related questions. For example, if the user inputs "What is the best diet to prevent colds?", the question is sent to the server. The terminal also has a function to display the answers and suggested menus sent from the server.

[0892] server

[0893] The server receives the question data sent from the user's device. Once the question data is received, the server retrieves user information (age, gender, medical history, etc.) from the user database based on the user ID. This user information and question data are then input into an artificial intelligence model to generate a customized answer.

[0894] Artificial Intelligence Model

[0895] The artificial intelligence model uses large-scale language models and other methods to generate customized answers based on question data and user information. This model has an algorithm that generates the best answer for the input prompt. An example of a generated answer is, "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds."

[0896] Sending answers to the user's device

[0897] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[0898] Menu suggestions and interface

[0899] The system also includes a means to suggest appropriate meal options based on user information and question data. The suggested menu is displayed on the user's device, providing an interface for ordering directly. For example, specific meal options such as "chicken soup," "vegetable salad," and "steamed salmon and broccoli" are suggested.

[0900] Hardware and Software

[0901] The system uses the following hardware and software:

[0902] User devices: smartphones, tablets

[0903] Server: User information management and AI model execution

[0904] Software: Python, requests library, large-scale language models

[0905] Specific examples

[0906] For example, if a user types into the app, "What is the best diet to prevent colds?", the AI ​​model generates a customized answer: "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds." Suggested menu items such as "chicken soup" and "a salad with lots of vegetables" are then provided, which the user can order directly from their device.

[0907] (Example of a prompt to input to a generative AI model)

[0908] User ID: 12345

[0909] Q: What is the best diet to prevent colds?

[0910] User information: 30-year-old male with a history of asthma

[0911] The system allows users to easily obtain and order dietary advice and meal menus adapted to their individual health conditions.

[0912] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0913] Step 1:

[0914] The user enters health-related questions into the device.

[0915] Input: A user asks a health-related question (e.g., "What is the best diet to prevent colds?")

[0916] Output: Input data displayed on the user's terminal

[0917] How it works: The user types a question through the interface of their smartphone or tablet, which the device then captures as data.

[0918] Step 2:

[0919] The user terminal sends the query data to the server.

[0920] Input: Question data entered by the user into the terminal

[0921] Output: The question data sent to the server

[0922] Specific operation: The terminal sends the question data entered by the user to the server as an HTTP request.

[0923] Step 3:

[0924] The server retrieves user information from the user database based on the user ID.

[0925] Input: User ID

[0926] Output: User information (age, gender, medical history, etc.)

[0927] Specific operation: The server executes a database query using the user ID in the request to obtain the corresponding user information.

[0928] Step 4:

[0929] The server combines the question data with user information and passes it to the artificial intelligence model.

[0930] Input: Question data, user information

[0931] Output: The prompt passed to the AI ​​model

[0932] Specific operation: The server combines the question data and user information into a single prompt sentence, and then inputs the prompt sentence into the artificial intelligence model.

[0933] Step 5:

[0934] An artificial intelligence model generates customized answers based on question data and user information.

[0935] Input: Prompt text (combined question data and user information)

[0936] Output: A customized answer (e.g., "A diet rich in vitamin C is particularly beneficial.")

[0937] What it does: The AI ​​model analyzes the prompt and runs an algorithm to generate the best answer.

[0938] Step 6:

[0939] The server sends the customized response to the user terminal.

[0940] Input: Customized Answer

[0941] Output: Customized answer data sent to the user's device

[0942] Specific operation: The server sends the generated answer to the user terminal as an HTTP response.

[0943] Step 7:

[0944] The user's device displays the customized answer.

[0945] Input: Customized answer data

[0946] Output: The answer that is displayed to the user.

[0947] Specific operation: The response data received by the device is displayed on the screen.

[0948] Step 8:

[0949] The server suggests an appropriate menu based on the user information and question data.

[0950] Input: User information, question data, generated answers

[0951] Output: Suggested menu items (e.g. "Chicken soup" or "Vegetable salad")

[0952] What it does: The server generates healthy menu options tailored to the user's information.

[0953] Step 9:

[0954] The user terminal displays the suggested menu and provides an interface for the user to place an order.

[0955] Input: Suggested menu

[0956] Output: The menu and ordering interface that is displayed on the user's screen.

[0957] Specific operation: Display the suggested menu and order button on the user's device, allowing the user to select a menu and place an order.

[0958] The above steps realize a system that allows users to receive customized advice in response to health-related questions and select and order a meal menu based on that advice.

[0959] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0960] The present invention provides a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end artificial intelligence model.

[0961] User Device

[0962] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[0963] Emotion Engine

[0964] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input, tone of voice, facial expressions, etc. to generate emotional data for the user. For example, it can determine whether the user is feeling stressed or depressed.

[0965] server

[0966] The server receives question data and emotion data sent from the user device. Once the question data is received, the server retrieves user information from a user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[0967] Artificial Intelligence Model

[0968] The AI ​​model generates customized answers based on question data, user information, and sentiment data using large-scale language models. The model has algorithms that generate the best answer for the input prompt. For example, the AI ​​model generates customized answers such as:

[0969] If a user types, "How do I prevent catching a cold?" and the emotion engine recognizes that the user is feeling stressed, the AI ​​model will generate an answer with adjusted tone and content: "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0970] Sending answers to the user's device

[0971] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[0972] Through the above process, the system of the present invention takes into account the user's emotional state and provides quick, accurate, and customized answers to health-related questions, supporting the user's health management.

[0973] As a specific example, if a user inputs a question such as, "Please tell me what dietary precautions I should take as a diabetic," and the emotion engine recognizes that the user is worried, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[0974] In this way, the present invention can provide optimal health advice tailored to each user's health and emotional state.

[0975] The processing flow will be explained below.

[0976] Step 1:

[0977] The user types a health-related question into an input field displayed on the device's interface, for example, "How do I prevent catching a cold?"

[0978] Step 2:

[0979] The device receives the user's input and simultaneously uses an emotion engine to analyze the user's emotional state, which can be inferred from the input text data, voice tone, or facial expressions.

[0980] Step 3:

[0981] The device sends the question data and the user's emotion data to the server, including the user ID.

[0982] Step 4:

[0983] The server receives a request from a user at an API endpoint and extracts the question data, emotion data, and user ID from the request body.

[0984] Step 5:

[0985] The server uses the user ID to retrieve user information from a user database, including age, gender, medical history, etc.

[0986] Step 6:

[0987] The server combines the acquired user information, question data, and emotional data to generate prompts to pass to the AI ​​model, which include details about the user's health and emotional state.

[0988] Step 7:

[0989] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data, user information, and sentiment data.

[0990] Step 8:

[0991] The server receives customized answers from the artificial intelligence model, with content and tone tailored based on the user's emotional state.

[0992] Step 9:

[0993] The server generates a response to send the customized answer to the user terminal.

[0994] Step 10:

[0995] The device receives the response from the server and displays a customized answer to the user, such as, "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[0996] Through these steps, users can receive customized health advice, which also takes into account the user's emotional state to provide better support.

[0997] Example 2

[0998] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0999] Today, there are many services that provide users with health information, but most only provide general information and few systems offer customized advice tailored to individual users' health and emotional states. Furthermore, while there is an increasing need for personalized advice that takes users' emotions into account, existing systems are limited in their ability to address this need. Therefore, there is a need for more accurate and personalized advice that takes into account the user's emotional state and individual health information.

[1000] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for integrating the acquired user information, question data, and emotion data to generate a prompt sentence to be input to the generative AI model, and means for generating a customized answer based on the question data, emotion data, and user information using the generative AI model. This makes it possible to quickly and accurately provide customized advice in response to a question entered by a user, taking into account the individual health condition and emotional state.

[1001] A "user terminal" is a device through which a user inputs health-related questions and communicates with the server.

[1002] "Question data" refers to data that indicates the content of health-related questions entered by the user.

[1003] "Emotional data" refers to data about a user's emotional state that is generated by analyzing the user's input, tone of voice, facial expressions, etc.

[1004] The "server" is a central processing unit for receiving question data and emotion data sent from a user terminal, generating prompt sentences based on the received data, and obtaining customized answers from the generative AI model.

[1005] "User ID" is an identifier that uniquely identifies a user.

[1006] A "user database" is a database that stores individual health information and medical history of users.

[1007] "User Information" refers to individual information necessary for providing health advice, such as the user's age, gender, and medical history.

[1008] A "prompt sentence" is a sentence format that integrates acquired user information, question data, and emotional data and is input into a generative AI model.

[1009] A "generative AI model" is an artificial intelligence model used to generate customized answers based on question data, emotion data, and user information.

[1010] "Customized answers" are personalized health advice generated using a generative AI model based on the user's individual information and emotional data.

[1011] The present invention is a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end generative AI model.

[1012] User Device

[1013] The user terminal is configured using a smartphone, computer, or similar device, and provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. It also has the function of receiving a customized answer from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?", the question is sent to the server.

[1014] Emotion Engine

[1015] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input content, voice tone, facial expressions, etc. to generate the user's emotion data. For example, it analyzes whether the user is feeling stressed when entering a question and generates this information as emotion data.

[1016] server

[1017] The server receives question data and emotion data sent from the user's device. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt sentence that is input into the generative AI model.

[1018] Specifically, the server generates a prompt like this:

[1019] If a user asks "How do I prevent catching a cold?" and the emotion engine detects "stress," provide a customized answer based on the user's information (age, gender, medical history).

[1020] Generative AI Models

[1021] A generative AI model uses a large-scale language model to generate customized answers based on question data, user information, and sentiment data. This model has an algorithm that generates the best answer for the input prompt. For example, the AI ​​model might generate a customized answer like this:

[1022] "Stress can increase your risk of catching a cold, so it's important to take time to relax, for example by doing deep breathing or yoga. It's also important to wash your hands properly and eat a balanced diet."

[1023] Sending answers to the user's device

[1024] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[1025] This system supports users in managing their health by allowing them to input health-related questions and providing quick and accurate customized answers that take into account their individual health and emotional state. For example, if a user inputs, "Please tell me about the diet I should be careful about as a diabetic," and the emotion engine recognizes the user's concerns, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[1026] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1027] Step 1:

[1028] User enters health questions

[1029] Input: User health question

[1030] Output: Question data

[1031] What happens: A user types a question into a smartphone or computer application: "How do I prevent catching a cold?"

[1032] Step 2:

[1033] The device sends the question data to the server.

[1034] Input: Question data, User ID

[1035] Output: Question data sent to the server

[1036] Specific operation: The user device sends the entered question to the server as an HTTP POST request. The sent data includes the question and the user ID.

[1037] Step 3:

[1038] The device generates emotion data using an emotion engine.

[1039] Input: User input, tone of voice, facial expressions, etc.

[1040] Output: Emotion data

[1041] How it works: The emotion engine analyzes the user's input, voice tone, and facial expressions to generate emotion data such as "stress" or "depression." The analysis results are sent to the server in JSON format.

[1042] Step 4:

[1043] The server receives the question data and emotion data.

[1044] Input: Question data, emotion data

[1045] Output: Question data and emotion data stored in a database on the server

[1046] Specific operation: The receiving API receives the data sent from the device and stores each piece of data in the database.

[1047] Step 5:

[1048] The server retrieves user information from the user database based on the user ID.

[1049] Input: User ID

[1050] Output: Obtained user information (age, gender, medical history, etc.)

[1051] Specific operation: Issues an SQL query to retrieve information such as the user's age, gender, and medical history from the database.

[1052] Step 6:

[1053] The server integrates question data, emotion data, and user information to generate prompt sentences to be input into the generative AI model.

[1054] Input: Question data, emotion data, user information

[1055] Output: prompt statement

[1056] Specific operation: The acquired data is integrated to generate a prompt sentence of the form, "If the user asks, 'How do I prevent a cold?' and the emotion engine recognizes the answer as 'stress,' provide a customized answer based on the user's information (age, gender, medical history)."

[1057] Step 7:

[1058] Server-generated prompts are fed into a generative AI model to obtain customized answers.

[1059] Input: prompt statement

[1060] Output: Customized answer

[1061] Specific operation: Sends a prompt to the API of the generated AI model via an HTTP POST request and receives the optimal answer from the AI ​​model.

[1062] Step 8:

[1063] The server generates the answer and sends it to the user's device.

[1064] Input: Customized Answer

[1065] Output: Answer sent to user terminal

[1066] Specific operation: A JSON containing the answer data is sent to the user's device as an HTTP response.

[1067] Step 9:

[1068] The user device displays a customized answer

[1069] Input: Customized Answer

[1070] Output: The answer shown to the user

[1071] Specific operation: The device displays the answer received from the server on the GUI, informing the user that "Stress can increase the risk of catching a cold, so it is important to take time to relax. For example, deep breathing or yoga are good ways to do this. It is also important to wash your hands properly and eat a balanced diet."

[1072] (Application example 2)

[1073] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1074] Conventional safety systems can only provide general advice, making it difficult to provide specific crime prevention advice tailored to the user's individual feelings and current situation. Therefore, it is necessary to improve the quality of information that helps users ensure their safety and provide more personalized crime prevention advice.

[1075] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1076] In this invention, the server includes means for a user to input a question at a user terminal, means for transmitting question data from the user terminal to the server, means for retrieving user information from an information database based on a user ID at the server, means for generating a customized answer based on the question data and user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for recognizing the user's emotions at the user terminal, means for retrieving the user's current location information, and means for generating a customized answer based on the question data, user information, emotions, and location information. This makes it possible to provide specific and appropriate crime prevention advice tailored to the user's current situation.

[1077] A "user terminal" is a device that provides an interface for a user to input questions or obtain emotion information.

[1078] "Question data" refers to data that indicates the content of a question entered by a user through a user terminal.

[1079] A "server" is a central computer system that processes query data, user information, emotion information, and location information.

[1080] "User information" refers to user attribute information obtained based on the user ID, including age, gender, medical history, etc.

[1081] "Emotional information" refers to data that indicates the user's emotional state, as analyzed from the user's input, tone of voice, facial expressions, etc.

[1082] "Location Information" is data that refers to a user's current geographic location.

[1083] An "artificial intelligence model" is a system with an algorithm that generates customized answers based on question data, user information, emotional information, and location information.

[1084] A "customized answer" is a specific answer to a user's question that is generated by taking into account user information, emotional information, and location information.

[1085] A "prompt" is a collection of data input to an artificial intelligence model, and refers to text that includes question data, user information, emotional information, and location information.

[1086] The present invention is a system that provides personalized crime prevention advice in response to a user's safety-related questions, taking into account the user's emotional information and location information. This system includes a "user terminal," an "emotion engine," a "server," and an "artificial intelligence model."

[1087] User Device

[1088] The user terminal takes the form of smart glasses. It provides an interface for users to input questions by voice and send the question data to the server. It also has the function of acquiring the user's emotional information and current location information. For example, if a user inputs a question such as "Is this area safe?", the voice data is collected.

[1089] Emotion Engine

[1090] The user device is equipped with an emotion engine that generates emotional information by analyzing the user's facial expressions and tone of voice, making it possible to understand the user's current emotional state, such as whether they are feeling anxious.

[1091] server

[1092] The server receives the question data, emotion information, and location information sent from the user terminal. The server then retrieves user information from the information database based on the user ID. The retrieved user information, emotion information, and location information are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[1093] Artificial Intelligence Model

[1094] The AI ​​model processes data using large-scale language models and other methods. The prompt includes question data, user information, emotional information, and location information. For example, if a user asks, "Is this area safe?" and the emotional engine recognizes that the user is feeling anxious, the AI ​​model will generate an answer with adjusted tone and content, such as, "The area around your current location is dangerous late at night. If you feel anxious, we recommend taking a taxi. The nearest taxi stand is ____."

[1095] Sending answers to the user's device

[1096] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate crime prevention advice based on their current situation and emotions.

[1097] Specific examples

[1098] Consider a case where a user is walking down a street at night and types the question "Is this area safe?" into their smart glasses. If the analysis indicates that the user is feeling uneasy, the server will use its AI model to generate a response such as "The area around your current location has a high crime rate. If you are uneasy, please use the nearest taxi stand (address: XXX)," and display this response on the smart glasses.

[1099] Prompt Sentence Examples

[1100] · Question: "Is this area safe?"

[1101] User information: age, gender, medical history, etc.

[1102] Emotional information: Anxiety

[1103] Location: Latitude 35.6895, Longitude 139.6917

[1104] By achieving the above, it becomes possible to provide specific and appropriate crime prevention advice that is tailored to the user's current situation.

[1105] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1106] Step 1:

[1107] The user types in a question.

[1108] Input: User voice question "Is this area safe?"

[1109] How it works: The user device converts speech into text data.

[1110] Output: Text data "Is this area safe?"

[1111] Step 2:

[1112] The user's device collects emotional information.

[1113] Input: User's voice tone and facial expressions

[1114] How it works: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state.

[1115] Output: Emotional information "anxiety"

[1116] Step 3:

[1117] The user device obtains the current location information.

[1118] Input: GPS sensor on the user device

[1119] How it works: The GPS sensor obtains the user's latitude and longitude.

[1120] Output: Location information "Latitude 35.6895, Longitude 139.6917"

[1121] Step 4:

[1122] The user terminal transmits question data, emotion information, and location information to the server.

[1123] Input: Question data, emotion information, location information

[1124] Operation: The user terminal sends these data to the server.

[1125] Output: Data package sent to the server

[1126] Step 5:

[1127] The server retrieves the user information.

[1128] Input: User ID

[1129] Operation: The server retrieves the corresponding user information from the information database.

[1130] Output: User information (e.g., age, gender, medical history, etc.)

[1131] Step 6:

[1132] The server consolidates the retrieved data and generates a prompt.

[1133] Input: Question data, user information, emotion information, location information

[1134] How it works: The server aggregates this data and creates prompts that are fed into an artificial intelligence model.

[1135] Output: Prompt "Is this area safe? User information: age, gender, current emotion (anxiety). Location information: latitude 35.6895, longitude 139.6917"

[1136] Step 7:

[1137] The server invokes the artificial intelligence model and provides the prompts.

[1138] Input: prompt

[1139] How it works: The server calls the artificial intelligence model and inputs a prompt.

[1140] Output: A customized answer from an artificial intelligence model

[1141] Step 8:

[1142] The server sends the customized response to the user terminal.

[1143] Input: Customized Answer

[1144] Operation: The server sends the generated answer to the user's device.

[1145] Output: The customized answer sent to the user's device

[1146] Step 9:

[1147] The user's device displays the customized answer.

[1148] Input: Customized Answer

[1149] Action: The user device displays the answer to the user visually or audibly.

[1150] Output: The user receives customized crime prevention advice.

[1151] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1152] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1153] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1154] [Fourth embodiment]

[1155] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1156] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1157] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1158] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1159] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1160] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1161] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1162] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1163] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1164] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1165] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1166] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1167] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1168] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health status and medical history. The system includes a user terminal, a server, and a back-end artificial intelligence model.

[1169] User Device

[1170] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[1171] server

[1172] The server receives the question data sent from the user terminal. Once the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the subsequent artificial intelligence model.

[1173] Artificial Intelligence Model

[1174] The artificial intelligence model generates customized answers based on question data and user information using large-scale language models, etc. This model has an algorithm that generates the best answer for the input prompt. As a specific example, the AI ​​model may generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, sufficient sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[1175] Sending answers to the user's device

[1176] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[1177] Through the above process, the system of the present invention provides users with quick, accurate, and customized answers to their health-related questions, supporting their health management.

[1178] For example, if a user inputs the question, "Please tell me about the dietary precautions I should take as a diabetic," the system will provide optimal dietary advice taking into account the user's age, gender, medical history (diabetes), etc. For example, specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided.

[1179] In this way, the present invention can provide optimal health advice according to the health conditions and lifestyle habits that differ for each user.

[1180] The processing flow will be explained below.

[1181] Step 1:

[1182] The user types a health-related question into an input field displayed on the device's interface, for example, "How can I prevent catching a cold?"

[1183] Step 2:

[1184] The device receives the user's input and sends the question data to the server via a pre-configured API endpoint, along with the user ID.

[1185] Step 3:

[1186] The server receives a request from the user at the API endpoint and extracts the question data and user ID from the request body.

[1187] Step 4:

[1188] The server uses the user ID to retrieve relevant user information (e.g., age, gender, medical history, etc.) from a user database.

[1189] Step 5:

[1190] The server combines the acquired user information with the question data to generate a prompt to be passed to the artificial intelligence model.

[1191] Step 6:

[1192] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data and user information.

[1193] Step 7:

[1194] The server receives the customized answer from the artificial intelligence model and then generates a response to send back to the user device.

[1195] Step 8:

[1196] The device receives the response from the server and displays a customized answer to the user, such as, "If you are a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are especially important for preventing colds."

[1197] Through these steps, users can receive customized health advice.

[1198] Example 1

[1199] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1200] Conventional health advice systems do not fully consider the user's individual health condition or past medical history, and therefore can only provide general advice, which lacks specificity and effectiveness for users. In addition, inefficient data processing makes it difficult to provide users with appropriate answers quickly.

[1201] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1202] In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for generating customized answers based on question data and user information using a generative AI model, and means for transmitting the customized answers to a user terminal, thereby enabling the prompt provision of specific and effective health advice based on each user's individual health condition and medical history.

[1203] A "user terminal" is a device that allows a user to input a question, transmit the question to a server, and receive and display a response from the server.

[1204] The "server" is a computer system that receives question data sent from a user terminal, retrieves user information from a user database, inputs it into a generative AI model, generates customized answers, and sends them to the user terminal.

[1205] "User ID" is an identifier that uniquely identifies a user.

[1206] A "user database" is a database for storing information such as a user's age, gender, and medical history.

[1207] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate appropriate answers based on question data and user information.

[1208] "Question data" refers to data entered by a user in response to a health-related question.

[1209] A "customized answer" is a personalized answer generated by a generative AI model based on the user's individual information.

[1210] A "prompt" is input data for a generative AI model, and includes question data and user information.

[1211] The present invention is a system that allows users to input health-related questions and provides personalized answers based on the individual user's health condition and medical history. The system includes a user terminal, a server, and a generative AI model.

[1212] User Device

[1213] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[1214] server

[1215] The server receives question data sent from the user terminal. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information and question data are input into the generative AI model. Specifically, the question data and user information are integrated and provided to the generative AI model as a prompt sentence. An example of a prompt sentence is, "Please tell me how to prevent colds for a 30-year-old man with a history of asthma."

[1216] Generative AI Models

[1217] Generative AI models use large-scale language models and other tools to generate customized answers based on question data and user information. These models have algorithms that generate the best answer for the input prompt. For example, an AI model might generate the answer, "For a 30-year-old man with a history of asthma, proper hand washing, adequate sleep, a balanced diet, and avoiding crowds are particularly important for preventing colds."

[1218] Sending answers to the user's device

[1219] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[1220] Specific examples

[1221] For example, if a user inputs a question such as, "Please tell me what dietary advice I should take into account as a diabetic," the system will provide optimal dietary advice taking into account information such as the user's age, gender, and medical history (diabetes). Specific, customized advice such as, "To manage diabetes, it is important to limit carbohydrates, choose low-sugar foods, and maintain consistent meal timings" is provided. Another example of a prompt sentence to be input into the generative AI model is, "Please tell me what is an appropriate diet for a 50-year-old woman with diabetes."

[1222] In this way, the system of the present invention can provide optimal health advice tailored to each user's different health conditions and lifestyle habits, allowing users to receive prompt and accurate personalized health support.

[1223] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1224] Step 1: Enter a question on the user's device

[1225] A user inputs a question about their health through the interface of the user terminal. For example, they input a question such as "How can I prevent catching a cold?" into the text box. The input question data is generated.

[1226] Input: User's health question

[1227] Output: Question data (e.g., "How do I prevent catching a cold?")

[1228] Step 2: Send query data to the server

[1229] The user device sends the entered question data to the server. Specifically, this data is sent as an HTTP request to the server's API endpoint.

[1230] Input: Question data

[1231] Output: Request sent to server

[1232] Step 3: Retrieving User Information on the Server

[1233] The server analyzes the received question data and retrieves user information from the user database based on the user ID. This extracts information such as the user's age, gender, and medical history. For example, it retrieves information about a 30-year-old male who has a history of asthma.

[1234] Input: Question data, User ID

[1235] Output: User information (e.g., age, gender, medical history)

[1236] Step 4: Generate answers using a generative AI model

[1237] The server combines the question data and user information to create a prompt. For example, a prompt such as "Please tell me how to prevent colds for a 30-year-old man with a history of asthma." This prompt is input into a generative AI model. The generative AI model (e.g., GPT-4) generates a customized answer based on the input prompt.

[1238] Input: Question data, user information

[1239] Output: Generated answer (e.g., "To prevent colds, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowds.")

[1240] Step 5: Returning response data to the server

[1241] The server receives the response data generated by the generative AI model and formats it as needed. For example, it formats the response data in JSON format and saves it in the appropriate response format.

[1242] Input: Generated Answer

[1243] Output: Formatted response data

[1244] Step 6: Sending the response from the server to the user device

[1245] The server then sends the formatted response data to the user terminal. Specifically, the response data is sent as an HTTP response.

[1246] Input: Formatted response data

[1247] Output: Send the answer to the user's device

[1248] Step 7: Display the answer on the user's device

[1249] The user's device analyzes the received response data and displays it on the user interface. The user can then view specific and appropriate advice. For example, the user can see the following response on their device: "To prevent catching a cold, it is especially important to wash your hands properly, get enough sleep, eat a balanced diet, and avoid crowded places."

[1250] Input: Formatted response data

[1251] Output: Displayed answer

[1252] (Application example 1)

[1253] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1254] Conventional food delivery systems have the problem of making it difficult to choose the right meal because they do not offer personalized menu suggestions based on the user's health condition or dietary restrictions. Even systems that offer advice based on health information have the problem of not being able to follow up with specific food suggestions.

[1255] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1256] In this invention, the server includes means for a user to input a health-related question at a user terminal, means for transmitting the question data from the user terminal to the server, means for retrieving user information from a user database based on a user ID at the server, means for generating a customized answer based on the question data and the user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for suggesting an appropriate menu based on the user information and the question data, and means for providing an interface for the user to order the suggested menu, thereby enabling appropriate menu selection based on the user's health condition and dietary restrictions and rapid ordering.

[1257] A "user terminal" is a device that allows a user to input health-related questions and display the answers.

[1258] "Question Data" refers to information about health-related questions entered by users.

[1259] A "server" is a device that has the function of receiving question data sent from a user and acquiring user information.

[1260] "User ID" is a unique identifier used to identify each user.

[1261] A "user database" is a database that holds information such as a user's age, gender, and medical history.

[1262] "User information" refers to detailed information about the user, such as their age, gender, and medical history.

[1263] An "artificial intelligence model" is an AI algorithm that generates customized answers based on question data and user information.

[1264] A "customized answer" is an answer generated based on the user's specific information (age, gender, medical history, etc.).

[1265] A "menu" is a selection of food or dishes suggested to a user.

[1266] An "interface" is the screen or operating means that a user uses to order the proposed menu.

[1267] The present invention is a system that allows users to input health-related questions and provides personalized health advice and appropriate meal menu suggestions based on the individual user's health condition and dietary restrictions. This system includes a user terminal, a server, and a back-end artificial intelligence model. The configuration and operation of the system are described in detail below.

[1268] User Device

[1269] The user terminal is a device such as a smartphone or tablet. The user can use the interface on this terminal to input health-related questions. For example, if the user inputs "What is the best diet to prevent colds?", the question is sent to the server. The terminal also has a function to display the answers and suggested menus sent from the server.

[1270] server

[1271] The server receives the question data sent from the user's device. Once the question data is received, the server retrieves user information (age, gender, medical history, etc.) from the user database based on the user ID. This user information and question data are then input into an artificial intelligence model to generate a customized answer.

[1272] Artificial Intelligence Model

[1273] The artificial intelligence model uses large-scale language models and other methods to generate customized answers based on question data and user information. This model has an algorithm that generates the best answer for the input prompt. An example of a generated answer is, "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds."

[1274] Sending answers to the user's device

[1275] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, who can then receive specific and appropriate advice based on their individual health condition.

[1276] Menu suggestions and interface

[1277] The system also includes a means to suggest appropriate meal options based on user information and question data. The suggested menu is displayed on the user's device, providing an interface for ordering directly. For example, specific meal options such as "chicken soup," "vegetable salad," and "steamed salmon and broccoli" are suggested.

[1278] Hardware and Software

[1279] The system uses the following hardware and software:

[1280] User devices: smartphones, tablets

[1281] Server: User information management and AI model execution

[1282] Software: Python, requests library, large-scale language models

[1283] Specific examples

[1284] For example, if a user types into the app, "What is the best diet to prevent colds?", the AI ​​model generates a customized answer: "For a 30-year-old man with a history of asthma, a diet rich in vitamin C is particularly effective in preventing colds." Suggested menu items such as "chicken soup" and "a salad with lots of vegetables" are then provided, which the user can order directly from their device.

[1285] (Example of a prompt to input to a generative AI model)

[1286] User ID: 12345

[1287] Q: What is the best diet to prevent colds?

[1288] User information: 30-year-old male with a history of asthma

[1289] The system allows users to easily obtain and order dietary advice and meal menus adapted to their individual health conditions.

[1290] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1291] Step 1:

[1292] The user enters health-related questions into the device.

[1293] Input: A user asks a health-related question (e.g., "What is the best diet to prevent colds?")

[1294] Output: Input data displayed on the user's terminal

[1295] How it works: The user types a question through the interface of their smartphone or tablet, which the device then captures as data.

[1296] Step 2:

[1297] The user terminal sends the query data to the server.

[1298] Input: Question data entered by the user into the terminal

[1299] Output: The question data sent to the server

[1300] Specific operation: The terminal sends the question data entered by the user to the server as an HTTP request.

[1301] Step 3:

[1302] The server retrieves user information from the user database based on the user ID.

[1303] Input: User ID

[1304] Output: User information (age, gender, medical history, etc.)

[1305] Specific operation: The server executes a database query using the user ID in the request to obtain the corresponding user information.

[1306] Step 4:

[1307] The server combines the question data with user information and passes it to the artificial intelligence model.

[1308] Input: Question data, user information

[1309] Output: The prompt passed to the AI ​​model

[1310] Specific operation: The server combines the question data and user information into a single prompt sentence, and then inputs the prompt sentence into the artificial intelligence model.

[1311] Step 5:

[1312] An artificial intelligence model generates customized answers based on question data and user information.

[1313] Input: Prompt text (combined question data and user information)

[1314] Output: A customized answer (e.g., "A diet rich in vitamin C is particularly beneficial.")

[1315] What it does: The AI ​​model analyzes the prompt and runs an algorithm to generate the best answer.

[1316] Step 6:

[1317] The server sends the customized response to the user terminal.

[1318] Input: Customized Answer

[1319] Output: Customized answer data sent to the user's device

[1320] Specific operation: The server sends the generated answer to the user terminal as an HTTP response.

[1321] Step 7:

[1322] The user's device displays the customized answer.

[1323] Input: Customized answer data

[1324] Output: The answer that is displayed to the user.

[1325] Specific operation: The response data received by the device is displayed on the screen.

[1326] Step 8:

[1327] The server suggests an appropriate menu based on the user information and question data.

[1328] Input: User information, question data, generated answers

[1329] Output: Suggested menu items (e.g. "Chicken soup" or "Vegetable salad")

[1330] What it does: The server generates healthy menu options tailored to the user's information.

[1331] Step 9:

[1332] The user terminal displays the suggested menu and provides an interface for the user to place an order.

[1333] Input: Suggested menu

[1334] Output: The menu and ordering interface that is displayed on the user's screen.

[1335] Specific operation: Display the suggested menu and order button on the user's device, allowing the user to select a menu and place an order.

[1336] The above steps realize a system that allows users to receive customized advice in response to health-related questions and select and order a meal menu based on that advice.

[1337] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1338] The present invention provides a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end artificial intelligence model.

[1339] User Device

[1340] The user terminal provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. The terminal also has the function of receiving a response from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?" into the terminal, the question is sent to the server.

[1341] Emotion Engine

[1342] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input, tone of voice, facial expressions, etc. to generate emotional data for the user. For example, it can determine whether the user is feeling stressed or depressed.

[1343] server

[1344] The server receives question data and emotion data sent from the user device. Once the question data is received, the server retrieves user information from a user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[1345] Artificial Intelligence Model

[1346] The AI ​​model generates customized answers based on question data, user information, and sentiment data using large-scale language models. The model has algorithms that generate the best answer for the input prompt. For example, the AI ​​model generates customized answers such as:

[1347] If a user types, "How do I prevent catching a cold?" and the emotion engine recognizes that the user is feeling stressed, the AI ​​model will generate an answer with adjusted tone and content: "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[1348] Sending answers to the user's device

[1349] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[1350] Through the above process, the system of the present invention takes into account the user's emotional state and provides quick, accurate, and customized answers to health-related questions, supporting the user's health management.

[1351] As a specific example, if a user inputs a question such as, "Please tell me what dietary precautions I should take as a diabetic," and the emotion engine recognizes that the user is worried, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[1352] In this way, the present invention can provide optimal health advice tailored to each user's health and emotional state.

[1353] The processing flow will be explained below.

[1354] Step 1:

[1355] The user types a health-related question into an input field displayed on the device's interface, for example, "How do I prevent catching a cold?"

[1356] Step 2:

[1357] The device receives the user's input and simultaneously uses an emotion engine to analyze the user's emotional state, which can be inferred from the input text data, voice tone, or facial expressions.

[1358] Step 3:

[1359] The device sends the question data and the user's emotion data to the server, including the user ID.

[1360] Step 4:

[1361] The server receives a request from a user at an API endpoint and extracts the question data, emotion data, and user ID from the request body.

[1362] Step 5:

[1363] The server uses the user ID to retrieve user information from a user database, including age, gender, medical history, etc.

[1364] Step 6:

[1365] The server combines the acquired user information, question data, and emotional data to generate prompts to pass to the AI ​​model, which include details about the user's health and emotional state.

[1366] Step 7:

[1367] The server invokes the AI ​​model, providing the generated prompt as input, which generates a customized answer based on the question data, user information, and sentiment data.

[1368] Step 8:

[1369] The server receives customized answers from the artificial intelligence model, with content and tone tailored based on the user's emotional state.

[1370] Step 9:

[1371] The server generates a response to send the customized answer to the user terminal.

[1372] Step 10:

[1373] The device receives the response from the server and displays a customized answer to the user, such as, "Stress can increase the risk of catching a cold, so it's important to take time to relax. For example, deep breathing and yoga are good ways to do this. It's also important to wash your hands properly and eat a balanced diet."

[1374] Through these steps, users can receive customized health advice, which also takes into account the user's emotional state to provide better support.

[1375] Example 2

[1376] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1377] Today, there are many services that provide users with health information, but most only provide general information and few systems offer customized advice tailored to individual users' health and emotional states. Furthermore, while there is an increasing need for personalized advice that takes users' emotions into account, existing systems are limited in their ability to address this need. Therefore, there is a need for more accurate and personalized advice that takes into account the user's emotional state and individual health information.

[1378] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring user information from a user database based on a user ID, means for integrating the acquired user information, question data, and emotion data to generate a prompt sentence to be input to the generative AI model, and means for generating a customized answer based on the question data, emotion data, and user information using the generative AI model. This makes it possible to quickly and accurately provide customized advice in response to a question entered by a user, taking into account the individual health condition and emotional state.

[1379] A "user terminal" is a device through which a user inputs health-related questions and communicates with the server.

[1380] "Question data" refers to data that indicates the content of health-related questions entered by the user.

[1381] "Emotional data" refers to data about a user's emotional state that is generated by analyzing the user's input, tone of voice, facial expressions, etc.

[1382] The "server" is a central processing unit for receiving question data and emotion data sent from a user terminal, generating prompt sentences based on the received data, and obtaining customized answers from the generative AI model.

[1383] "User ID" is an identifier that uniquely identifies a user.

[1384] A "user database" is a database that stores individual health information and medical history of users.

[1385] "User Information" refers to individual information necessary for providing health advice, such as the user's age, gender, and medical history.

[1386] A "prompt sentence" is a sentence format that integrates acquired user information, question data, and emotional data and is input into a generative AI model.

[1387] A "generative AI model" is an artificial intelligence model used to generate customized answers based on question data, emotion data, and user information.

[1388] "Customized answers" are personalized health advice generated using a generative AI model based on the user's individual information and emotional data.

[1389] The present invention is a system that allows users to input health-related questions and provides personalized answers by recognizing the individual user's health condition, medical history, and even the user's emotions. The system includes a user terminal, an emotion engine, a server, and a back-end generative AI model.

[1390] User Device

[1391] The user terminal is configured using a smartphone, computer, or similar device, and provides an interface for users to input health-related questions. When a user inputs a question, the data can be sent to the server. It also has the function of receiving a customized answer from the server and displaying it to the user. For example, if a user inputs "How can I prevent catching a cold?", the question is sent to the server.

[1392] Emotion Engine

[1393] The user device is equipped with an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input content, voice tone, facial expressions, etc. to generate the user's emotion data. For example, it analyzes whether the user is feeling stressed when entering a question and generates this information as emotion data.

[1394] server

[1395] The server receives question data and emotion data sent from the user's device. When the question data is received, the server retrieves user information from the user database based on the user ID. This user information includes age, gender, medical history, etc. The retrieved user information, emotion data, and question data are integrated to generate a prompt sentence that is input into the generative AI model.

[1396] Specifically, the server generates a prompt like this:

[1397] If a user asks "How do I prevent catching a cold?" and the emotion engine detects "stress," provide a customized answer based on the user's information (age, gender, medical history).

[1398] Generative AI Models

[1399] A generative AI model uses a large-scale language model to generate customized answers based on question data, user information, and sentiment data. This model has an algorithm that generates the best answer for the input prompt. For example, the AI ​​model might generate a customized answer like this:

[1400] "Stress can increase your risk of catching a cold, so it's important to take time to relax, for example by doing deep breathing or yoga. It's also important to wash your hands properly and eat a balanced diet."

[1401] Sending answers to the user's device

[1402] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate advice based on their individual health and emotional state.

[1403] This system supports users in managing their health by allowing them to input health-related questions and providing quick and accurate customized answers that take into account their individual health and emotional state. For example, if a user inputs, "Please tell me about the diet I should be careful about as a diabetic," and the emotion engine recognizes the user's concerns, the AI ​​model will provide a warm response such as, "Limiting carbohydrates is important for managing diabetes, but don't worry. It's a good idea to actively choose low-sugar foods. It's also important to consult with your doctor regularly."

[1404] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1405] Step 1:

[1406] User enters health questions

[1407] Input: User health question

[1408] Output: Question data

[1409] What happens: A user types a question into a smartphone or computer application: "How do I prevent catching a cold?"

[1410] Step 2:

[1411] The device sends the question data to the server.

[1412] Input: Question data, User ID

[1413] Output: Question data sent to the server

[1414] Specific operation: The user device sends the entered question to the server as an HTTP POST request. The sent data includes the question and the user ID.

[1415] Step 3:

[1416] The device generates emotion data using an emotion engine.

[1417] Input: User input, tone of voice, facial expressions, etc.

[1418] Output: Emotion data

[1419] How it works: The emotion engine analyzes the user's input, voice tone, and facial expressions to generate emotion data such as "stress" or "depression." The analysis results are sent to the server in JSON format.

[1420] Step 4:

[1421] The server receives the question data and emotion data.

[1422] Input: Question data, emotion data

[1423] Output: Question data and emotion data stored in a database on the server

[1424] Specific operation: The receiving API receives the data sent from the device and stores each piece of data in the database.

[1425] Step 5:

[1426] The server retrieves user information from the user database based on the user ID.

[1427] Input: User ID

[1428] Output: Obtained user information (age, gender, medical history, etc.)

[1429] Specific operation: Issues an SQL query to retrieve information such as the user's age, gender, and medical history from the database.

[1430] Step 6:

[1431] The server integrates question data, emotion data, and user information to generate prompt sentences to be input into the generative AI model.

[1432] Input: Question data, emotion data, user information

[1433] Output: prompt statement

[1434] Specific operation: The acquired data is integrated to generate a prompt sentence of the form, "If the user asks, 'How do I prevent a cold?' and the emotion engine recognizes the answer as 'stress,' provide a customized answer based on the user's information (age, gender, medical history)."

[1435] Step 7:

[1436] Server-generated prompts are fed into a generative AI model to obtain customized answers.

[1437] Input: prompt statement

[1438] Output: Customized answer

[1439] Specific operation: Sends a prompt to the API of the generated AI model via an HTTP POST request and receives the optimal answer from the AI ​​model.

[1440] Step 8:

[1441] The server generates the answer and sends it to the user's device.

[1442] Input: Customized Answer

[1443] Output: Answer sent to user terminal

[1444] Specific operation: A JSON containing the answer data is sent to the user's device as an HTTP response.

[1445] Step 9:

[1446] The user device displays a customized answer

[1447] Input: Customized Answer

[1448] Output: The answer shown to the user

[1449] Specific operation: The device displays the answer received from the server on the GUI, informing the user that "Stress can increase the risk of catching a cold, so it is important to take time to relax. For example, deep breathing or yoga are good ways to do this. It is also important to wash your hands properly and eat a balanced diet."

[1450] (Application example 2)

[1451] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1452] Conventional safety systems can only provide general advice, making it difficult to provide specific crime prevention advice tailored to the user's individual feelings and current situation. Therefore, it is necessary to improve the quality of information that helps users ensure their safety and provide more personalized crime prevention advice.

[1453] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1454] In this invention, the server includes means for a user to input a question at a user terminal, means for transmitting question data from the user terminal to the server, means for retrieving user information from an information database based on a user ID at the server, means for generating a customized answer based on the question data and user information using an artificial intelligence model, means for transmitting the customized answer to the user terminal, means for displaying the customized answer at the user terminal, means for recognizing the user's emotions at the user terminal, means for retrieving the user's current location information, and means for generating a customized answer based on the question data, user information, emotions, and location information. This makes it possible to provide specific and appropriate crime prevention advice tailored to the user's current situation.

[1455] A "user terminal" is a device that provides an interface for a user to input questions or obtain emotion information.

[1456] "Question data" refers to data that indicates the content of a question entered by a user through a user terminal.

[1457] A "server" is a central computer system that processes query data, user information, emotion information, and location information.

[1458] "User information" refers to user attribute information obtained based on the user ID, including age, gender, medical history, etc.

[1459] "Emotional information" refers to data that indicates the user's emotional state, as analyzed from the user's input, tone of voice, facial expressions, etc.

[1460] "Location Information" is data that refers to a user's current geographic location.

[1461] An "artificial intelligence model" is a system with an algorithm that generates customized answers based on question data, user information, emotional information, and location information.

[1462] A "customized answer" is a specific answer to a user's question that is generated by taking into account user information, emotional information, and location information.

[1463] A "prompt" is a collection of data input to an artificial intelligence model, and refers to text that includes question data, user information, emotional information, and location information.

[1464] The present invention is a system that provides personalized crime prevention advice in response to a user's safety-related questions, taking into account the user's emotional information and location information. This system includes a "user terminal," an "emotion engine," a "server," and an "artificial intelligence model."

[1465] User Device

[1466] The user terminal takes the form of smart glasses. It provides an interface for users to input questions by voice and send the question data to the server. It also has the function of acquiring the user's emotional information and current location information. For example, if a user inputs a question such as "Is this area safe?", the voice data is collected.

[1467] Emotion Engine

[1468] The user device is equipped with an emotion engine that generates emotional information by analyzing the user's facial expressions and tone of voice, making it possible to understand the user's current emotional state, such as whether they are feeling anxious.

[1469] server

[1470] The server receives the question data, emotion information, and location information sent from the user terminal. The server then retrieves user information from the information database based on the user ID. The retrieved user information, emotion information, and location information are integrated to generate a prompt that is input into the subsequent artificial intelligence model.

[1471] Artificial Intelligence Model

[1472] The AI ​​model processes data using large-scale language models and other methods. The prompt includes question data, user information, emotional information, and location information. For example, if a user asks, "Is this area safe?" and the emotional engine recognizes that the user is feeling anxious, the AI ​​model will generate an answer with adjusted tone and content, such as, "The area around your current location is dangerous late at night. If you feel anxious, we recommend taking a taxi. The nearest taxi stand is ____."

[1473] Sending answers to the user's device

[1474] The server then sends the generated customized answer to the user's device, which then displays the customized answer to the user, allowing the user to receive specific and appropriate crime prevention advice based on their current situation and emotions.

[1475] Specific examples

[1476] Consider a case where a user is walking down a street at night and types the question "Is this area safe?" into their smart glasses. If the analysis indicates that the user is feeling uneasy, the server will use its AI model to generate a response such as "The area around your current location has a high crime rate. If you are uneasy, please use the nearest taxi stand (address: XXX)," and display this response on the smart glasses.

[1477] Prompt Sentence Examples

[1478] · Question: "Is this area safe?"

[1479] User information: age, gender, medical history, etc.

[1480] Emotional information: Anxiety

[1481] Location: Latitude 35.6895, Longitude 139.6917

[1482] By achieving the above, it becomes possible to provide specific and appropriate crime prevention advice that is tailored to the user's current situation.

[1483] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1484] Step 1:

[1485] The user types in a question.

[1486] Input: User voice question "Is this area safe?"

[1487] How it works: The user device converts speech into text data.

[1488] Output: Text data "Is this area safe?"

[1489] Step 2:

[1490] The user's device collects emotional information.

[1491] Input: User's voice tone and facial expressions

[1492] How it works: The emotion engine analyzes voice tone and facial expressions to recognize the user's emotional state.

[1493] Output: Emotional information "anxiety"

[1494] Step 3:

[1495] The user device obtains the current location information.

[1496] Input: GPS sensor on the user device

[1497] How it works: The GPS sensor obtains the user's latitude and longitude.

[1498] Output: Location information "Latitude 35.6895, Longitude 139.6917"

[1499] Step 4:

[1500] The user terminal transmits question data, emotion information, and location information to the server.

[1501] Input: Question data, emotion information, location information

[1502] Operation: The user terminal sends these data to the server.

[1503] Output: Data package sent to the server

[1504] Step 5:

[1505] The server retrieves the user information.

[1506] Input: User ID

[1507] Operation: The server retrieves the corresponding user information from the information database.

[1508] Output: User information (e.g., age, gender, medical history, etc.)

[1509] Step 6:

[1510] The server consolidates the retrieved data and generates a prompt.

[1511] Input: Question data, user information, emotion information, location information

[1512] How it works: The server aggregates this data and creates prompts that are fed into an artificial intelligence model.

[1513] Output: Prompt "Is this area safe? User information: age, gender, current emotion (anxiety). Location information: latitude 35.6895, longitude 139.6917"

[1514] Step 7:

[1515] The server invokes the artificial intelligence model and provides the prompts.

[1516] Input: prompt

[1517] How it works: The server calls the artificial intelligence model and inputs a prompt.

[1518] Output: A customized answer from an artificial intelligence model

[1519] Step 8:

[1520] The server sends the customized response to the user terminal.

[1521] Input: Customized Answer

[1522] Operation: The server sends the generated answer to the user's device.

[1523] Output: The customized answer sent to the user's device

[1524] Step 9:

[1525] The user's device displays the customized answer.

[1526] Input: Customized Answer

[1527] Action: The user device displays the answer to the user visually or audibly.

[1528] Output: The user receives customized crime prevention advice.

[1529] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1530] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1531] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1532] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1533] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1534] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1535] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1536] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1537] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1538] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1539] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1540] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1541] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1542] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1543] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1544] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1545] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1546] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1547] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1548] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1549] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1550] The following is further disclosed regarding the above embodiment.

[1551] (Claim 1)

[1552] a means for a user to input a health question at a user terminal;

[1553] A means for transmitting question data from a user terminal to a server;

[1554] A means for acquiring user information from a user database based on the user ID in the server;

[1555] means for generating customized answers based on the question data and user information using an artificial intelligence model;

[1556] means for transmitting the customized response to the user terminal;

[1557] means for displaying the customized answer at the user terminal;

[1558] A system including:

[1559] (Claim 2)

[1560] The system according to claim 1, further comprising means for integrating the question data and the data relating to the user information in the server and passing the data to the artificial intelligence model.

[1561] (Claim 3)

[1562] 2. The system of claim 1, wherein the artificial intelligence model is a language model, and further comprising means for invoking the artificial intelligence model in a server, generating a prompt including question data and user information, and providing the prompt to the artificial intelligence model.

[1563] "Example 1"

[1564] (Claim 1)

[1565] a means for a user to input a health question at a user terminal;

[1566] A means for transmitting question data from a user terminal to a server;

[1567] A means for acquiring user information from a user database based on the user ID in the server;

[1568] a means for generating customized answers based on question data and user information using a generative AI model;

[1569] means for transmitting the customized response to the user terminal;

[1570] means for displaying the customized answer at the user terminal;

[1571] A system including:

[1572] (Claim 2)

[1573] The system of claim 1, further comprising means for integrating the question data and data related to user information in the server and passing the data to the generative AI model.

[1574] (Claim 3)

[1575] The system of claim 1, wherein the generative AI model is a language model, and further comprising means for invoking the generative AI model in a server, generating a prompt including question data and user information, and providing the prompt to the generative AI model.

[1576] "Application Example 1"

[1577] (Claim 1)

[1578] a means for a user to input a health question at a user terminal;

[1579] A means for transmitting question data from a user terminal to a server;

[1580] A means for acquiring user information from a user database based on the user ID in the server;

[1581] means for generating customized answers based on the question data and user information using an artificial intelligence model;

[1582] means for transmitting the customized response to the user terminal;

[1583] means for displaying the customized answer at the user terminal;

[1584] A means to suggest appropriate menus based on user information and question data,

[1585] means for providing an interface for a user to order from the suggested menu;

[1586] A system including:

[1587] (Claim 2)

[1588] The system according to claim 1, further comprising means for integrating the question data and the data relating to the user information in the server and passing the data to the artificial intelligence model.

[1589] (Claim 3)

[1590] 2. The system of claim 1, wherein the artificial intelligence model is a language model, and further comprising means for invoking the artificial intelligence model in a server, generating a prompt including question data and user information, and providing the prompt to the artificial intelligence model.

[1591] "Example 2: Combining Emotion Engines"

[1592] (Claim 1)

[1593] a means for a user to input a health question at a user terminal;

[1594] A means for transmitting question data from a user terminal to a server;

[1595] A means for analyzing user emotions and generating emotion data in a user terminal;

[1596] means for transmitting emotion data to a server;

[1597] A means for acquiring user information from a user database based on the user ID in the server;

[1598] A means for integrating the acquired user information, question data, and emotion data to generate a prompt sentence to be input to the generative AI model;

[1599] a means for generating customized answers based on question data, sentiment data, and user information using a generative AI model;

[1600] means for transmitting the customized response to the user terminal;

[1601] means for displaying the customized answer at the user terminal;

[1602] A system including:

[1603] (Claim 2)

[1604] 2. The system of claim 1, further comprising: means for aggregating the question data, emotion data, and data related to user information in the server and passing the data to the artificial intelligence model.

[1605] (Claim 3)

[1606] 2. The system of claim 1, wherein the artificial intelligence model is a language model, and further comprising means for invoking the artificial intelligence model in a server, generating a prompt including question data, emotion data, and user information, and providing the prompt to the artificial intelligence model.

[1607] "Application example 2 when combining emotion engines"

[1608] (Claim 1)

[1609] a means for a user to input a question at a user terminal;

[1610] A means for transmitting question data from a user terminal to a server;

[1611] A means for acquiring user information from an information database based on the user ID in the server;

[1612] means for generating customized answers based on the question data and user information using an artificial intelligence model;

[1613] means for transmitting the customized response to the user terminal;

[1614] means for displaying the customized answer at the user terminal;

[1615] a means for recognizing user emotions at the user terminal;

[1616] A means for obtaining the user's current location information;

[1617] a means for generating customized answers based on question data, user information, sentiment, and location information;

[1618] A system including:

[1619] (Claim 2)

[1620] The system according to claim 1, further comprising means for integrating the question data with the user information and emotion data in the server and passing the integrated data to the artificial intelligence model.

[1621] (Claim 3)

[1622] 2. The system of claim 1, wherein the artificial intelligence model is a language model, and further comprising means for invoking the artificial intelligence model in a server, generating a prompt including question data, user information and emotions, and providing the prompt to the artificial intelligence model. [Explanation of symbols]

[1623] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input a health question at a user terminal; A means for transmitting question data from a user terminal to a server; A means for acquiring user information from a user database based on the user ID in the server; means for generating customized answers based on the question data and user information using an artificial intelligence model; means for transmitting the customized response to the user terminal; means for displaying the customized answer at the user terminal; A system including:

2. The system according to claim 1, further comprising means for integrating the question data and data relating to user information in the server and passing the data to the artificial intelligence model.

3. 2. The system of claim 1, wherein the artificial intelligence model is a language model, and further comprising means for invoking the artificial intelligence model in a server, generating a prompt including question data and user information, and providing the prompt to the artificial intelligence model.

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